{"as_of":"2026-08-15T06:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1ccce1c77c6759e96c6e7511d99de6740c73864f8a55bcaa6b298f9ec982fb6f","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:16:41.518320Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.03595/citation-record","integrity":"/paper/1908.03595/integrity","json":"/paper/1908.03595/citation-record.json","paper":"/paper/1908.03595"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.579093Z","title":"Learning from class-imbalanced data: Review of methods and applications.Expert Systems with Applications, 73:220–239, 2017","venue":null,"work_id":"99c63131-463d-47df-a143-eb8fdea52b7a","year":2017},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.221300Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:8893f2ae6fa9f763b31daf322a31a7bbed9278d55c2cf07db8e74426c7f37931","observation_id":"d6dc61e4-16fb-45ab-8d30-af53ca43a1d1","resolution":{"observed_at":"2026-08-14T14:16:42.583610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.564983Z","title":"A hybrid feature selection with ensemble classiﬁcation for imbalanced healthcare data: A case study for brain tumor diagnosis.IEEE Access, 4:9145– 9154, 2016","venue":null,"work_id":"76821013-df7f-4b9e-a7ca-cef68b15511c","year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.226489Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:664c52aca2b15e6f7effbcb7ba0d63d626bcae04b21c1cded994dc243fbbfa29","observation_id":"d468bfff-b922-4c6b-a602-f04dc0942e71","resolution":{"observed_at":"2026-08-14T14:16:42.570497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.550443Z","title":null,"venue":null,"work_id":"d2611cec-8f4d-4895-9dbb-f8c7e7ec3ede","year":2013},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.231441Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:f9fc84175ec501cfef93bf7366f7902d5689f95d8942993162fd3d4124dac6d1","observation_id":"cc86b978-7f84-44fc-b5ec-5124b4e9a634","resolution":{"observed_at":"2026-08-14T14:16:42.555124Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.536839Z","title":"Rosefw-rf: the winner algorithm for the ecbdl’14 big data competition: an extremely imbalanced big data bioinformatics problem.Knowledge-Based Systems, 87:69–79, 2015","venue":null,"work_id":"ea56f8a2-a6a2-44d8-86d4-b13ef08a5910","year":2015},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.236625Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:e58f6f04e34020255504a84f718df9366795479b76de26a421fd3dbee064b9f5","observation_id":"54321fec-b31e-40bd-89b1-41cf93c29702","resolution":{"observed_at":"2026-08-14T14:16:42.541130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.522036Z","title":null,"venue":null,"work_id":"01ff8e52-f75c-4311-a4d8-265053656efc","year":2019},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.240921Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:497af47b660372d3a034e16cad5d0b63072c9fbc51ed538b8e2b3178116355e1","observation_id":"e316dc48-9117-4719-afe3-700965feaac5","resolution":{"observed_at":"2026-08-14T14:16:42.527156Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.508535Z","title":"A study on combining dynamic selection and data preprocessing for imbalance learning.Neurocomputing, 286:179–192, 2018","venue":null,"work_id":"9933b699-bcc8-43c8-958e-37e10b09bbb3","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.245783Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:6148154551301707b3a1c3b300d1d9a0289d45dc50bde20ab91cc0e6e851143c","observation_id":"41df9be8-3f40-44e5-b334-edd7bd4a7061","resolution":{"observed_at":"2026-08-14T14:16:42.512931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.495631Z","title":"Combining multiple algorithms in classiﬁer ensembles using generalized mixture functions.Neurocomputing, 313:402–414, 2018","venue":null,"work_id":"e15c4919-4d1a-4d0e-bf7a-959337fe3663","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.250614Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:24b2fdc8ef55226b0f5528a5e14b8bb7b19a68a09d999aaf6cc3bfc5b79e1ae5","observation_id":"4071c355-2bd2-4bcc-ae69-c009a3eb864a","resolution":{"observed_at":"2026-08-14T14:16:42.500002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.482403Z","title":"A framework for dynamic classiﬁer selection oriented by the classiﬁcation problem diﬃculty","venue":null,"work_id":"2619c3d1-ed3d-45e7-8422-ffaf67a0bae1","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.254721Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:b18410778288223d635d5b7e27ff833ac7437c9ab72746904f691d2a49aab3c7","observation_id":"26025300-99a9-4317-842b-c0b064b709e2","resolution":{"observed_at":"2026-08-14T14:16:42.487333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.258511Z","title":"Bayesian reasoning and machine learning","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.258511Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:54e6808af825870471c118c50ef018a7a6efdf1162e730ee9f6376b6f9b8c897","observation_id":"28f8d4c4-d5e9-4106-aef7-5aedb5bfedf9","resolution":{"observed_at":"2026-08-14T14:16:41.258511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.459623Z","title":"Robust text-independent speaker identiﬁcation using gaussian mixture speaker models.IEEE transactions on speech and audio processing, 3(1):72–83, 1995","venue":null,"work_id":"99bf5e81-847f-4685-b49d-c62596dc2e37","year":1995},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.262850Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:f6ecd76385d4b005e6740b0fe394a367df2792d3206a3728525ad5bc2781d666","observation_id":"70af3859-a828-4801-81d8-373ad4716ca1","resolution":{"observed_at":"2026-08-14T14:16:42.465775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.445975Z","title":"Learning characteristics of stochastic-gradient-descent algorithms: A general study, analysis, and critique.Signal processing, 6(2):113–133, 1984","venue":null,"work_id":"48903bf2-517f-408e-a3e3-23644d9f00da","year":1984},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.266732Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:09a1defaad5e1f422fc819e33532761671a014bed4d35b89398d2c966eb45f4d","observation_id":"07419da0-b3b4-4043-a693-1f0d43a03137","resolution":{"observed_at":"2026-08-14T14:16:42.450803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.430507Z","title":"Under- standing deep learning requires rethinking generalization","venue":null,"work_id":"249df72f-1c80-4b8c-858d-b90cd5e3d312","year":2017},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.270797Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:480fc277a93707cb470524575029180bfd989aa282b360fb4835e931e3320ddd","observation_id":"67caffc1-a243-4d36-a854-b6067331d815","resolution":{"observed_at":"2026-08-14T14:16:42.436884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.275774Z","title":"Deep learning in neural networks: An overview","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.275774Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:3fd50e2f64a9e7b418f5a8a5a95ad20a264de57f82abf673a11f3d0da3111678","observation_id":"34557dc2-231a-4afa-ae00-ea24fe0eb094","resolution":{"observed_at":"2026-08-14T14:16:41.275774Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.409830Z","title":"Optimization methods for large-scale ma- chine learning","venue":null,"work_id":"203b302f-b6c6-4985-825a-e04e8d033b5a","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.279909Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:02eafaf72b3b45d141bbe2d70ec3b8b60eb8199416c4f110ab08e0d430849478","observation_id":"8db2b384-dae7-45ef-972d-e76d0a88e3d2","resolution":{"observed_at":"2026-08-14T14:16:42.414209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.395196Z","title":"Xgboost: A scalable tree boosting system","venue":null,"work_id":"2b38ae1e-cfac-4113-aeb1-a4e34b92633a","year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.285198Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:f2cced6ba8f4fb6f9613067ce4513aa040d977e68615480af4660c4e535e41d6","observation_id":"97e828e6-4566-4fd5-92c2-327415b85d3b","resolution":{"observed_at":"2026-08-14T14:16:42.399923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.380327Z","title":"Focal loss for dense object detection","venue":null,"work_id":"740981a0-52bc-4742-99f4-929699454e1c","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.289271Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:234ec56bc26d78c58f5a6f6adf3ab41f6c3069ddbc38a1ab2f7413257633e696","observation_id":"9a8aedab-91fa-4882-8a85-3530be359e32","resolution":{"observed_at":"2026-08-14T14:16:42.385186Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.366591Z","title":"Imbalance-xgboost: Leveraging weighted and focal losses for binary label-imbalanced classiﬁcation with xgboost.Pattern Recognition Letters, 2020","venue":null,"work_id":"34734bf9-c135-40a4-917b-abafd0567840","year":2020},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.293604Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:8a431aba8a5486757fc8bdf1a7e906bea68177e4c9563e507cef99ef0853f039","observation_id":"d84edb41-c124-480c-b85b-bb9ad9666513","resolution":{"observed_at":"2026-08-14T14:16:42.370964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.354658Z","title":"Lightgbm: A highly eﬃcient gradient boosting decision tree","venue":null,"work_id":"7429afdb-c219-43e1-ab05-0a491f38ed7d","year":2017},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.297747Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:4747e5bf53a207b25d9f25c22b66f52fa47d2095348b44c2f6e49cf0450cad7c","observation_id":"9e331d7e-3a44-4c47-8997-df5406e87762","resolution":{"observed_at":"2026-08-14T14:16:42.358756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.340450Z","title":"Handling data irregularities in classiﬁcation: Foundations, trends, and future challenges.Pattern Recognition, 81:674–693, 2018","venue":null,"work_id":"9be400bf-51dd-4ead-b27f-04657b5227ba","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.301792Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:23722454b18366571c55427285a70b81bf6e620253c9f29ce5ff299d9cb68949","observation_id":"dafa296d-0f02-493c-84cd-386fabdf5992","resolution":{"observed_at":"2026-08-14T14:16:42.346129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.325930Z","title":"Analysing the classiﬁcation of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches.Knowledge-based systems, 42:97–110, 2013","venue":null,"work_id":"a91fe730-acec-43a7-b902-a88941e4157a","year":2013},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.305804Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:7b29ad1cc33c317e51e311af003f652729ab2df3a25437687a88141ec03480a7","observation_id":"f29df517-3e25-472a-bda8-c541ed468b13","resolution":{"observed_at":"2026-08-14T14:16:42.331193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.312867Z","title":"Learning from imbalanced data: open challenges and future directions","venue":null,"work_id":"7a7ab233-d8c9-498a-9a5f-56035285b732","year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.309832Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:9b5930ef29e917db6bbe20e15d30dad6b814cb0c609e6790fefc97a974653715","observation_id":"3b9d32dd-d407-4ca6-8805-9b1b64e78438","resolution":{"observed_at":"2026-08-14T14:16:42.317554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.06048","last_updated":"2016-08-22T04:27:28Z","snapshot_observed_at":"2026-08-14T21:43:19.902626Z","submitted_at":"2016-08-22T04:27:28Z","title":"Survey of resampling techniques for improving classification performance in unbalanced datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.06048","snapshot_observed_at":"2026-08-14T14:16:41.314135Z","title":"Survey of resampling techniques for improving classiﬁcation performance in unbalanced datasets","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.314135Z"},"links":{"cited_paper":"/paper/1608.06048","citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:422fe3a9347d4bd6a8a717a691128d602ac76a10009366ad5531fbd060610e53","observation_id":"2ba22b04-12db-451a-9c01-9f922a277175","resolution":{"observed_at":"2026-08-14T14:16:41.314135Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.298430Z","title":"Cost-sensitive learning of deep feature representations from imbalanced data.IEEE transactions on neural networks and learning systems, 2017","venue":null,"work_id":"5c067ebf-20e9-420e-abba-5e36ca757759","year":2017},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.319587Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:bd4912e5c58b04e1eda6cf5557b0a0f3ea1d5750dc1e29b59ca0c867fc2f17b0","observation_id":"161dd894-cbf1-4fea-8fa6-70ccce111e78","resolution":{"observed_at":"2026-08-14T14:16:42.304106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.285626Z","title":"Near-bayesian support vector machines for imbalanced data classiﬁcation with equal or unequal misclassiﬁcation costs.Neural Networks, 70:39–52, 2015","venue":null,"work_id":"864e0e05-5370-4d02-b1f3-989bc2eef31d","year":2015},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.324780Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:83a431eb27259f142919d317aa46c335aad5514c31189a0a4d55378e495dee8d","observation_id":"ca5f970f-d2ac-4914-b4ba-e6d98951c73b","resolution":{"observed_at":"2026-08-14T14:16:42.290175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.272209Z","title":"Class-speciﬁc extreme learning machine for handling binary class imbalance problem.Neural Networks, 105:206–217, 2018","venue":null,"work_id":"3fbcfc39-7f6e-4aca-ac9b-ed81e96cce6e","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.329566Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:612056cf0ca582d312a490a75be6133e0368c6852bd4689e548cdd14a09e8b65","observation_id":"d36e337a-1686-49a6-87b5-b829184a4817","resolution":{"observed_at":"2026-08-14T14:16:42.276740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.258117Z","title":"Online sequential class-speciﬁc extreme learning machine for binary imbalanced learning.Neural Networks, 119:235–248, 2019","venue":null,"work_id":"2152328c-373f-4e2d-86e8-8b77750d1564","year":2019},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.334518Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:3e17c0cf4a50d6cac5a16a4ee3f01d0eaf70012815ada356299739672de6eb91","observation_id":"7b6e8d46-e1c6-44cb-9c82-5a88b3ecc13c","resolution":{"observed_at":"2026-08-14T14:16:42.264117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.244511Z","title":"One-class versus binary classi- ﬁcation: Which and when? In Machine Learning and Applications (ICMLA), 2012 11th International Conference on, volume 2, pages 102–106","venue":null,"work_id":"ce100876-1300-447b-a62e-2ec5691e3abe","year":2012},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.338834Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:291a9694e23b6bb3e6039b3608348cdf51671243eefcf5d38e185310fb26cb9e","observation_id":"227b32c8-ed0e-4f48-9cd1-15bdcde11ca6","resolution":{"observed_at":"2026-08-14T14:16:42.249647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.229217Z","title":"Feature learning with a divergence-encouraging autoencoder for imbalanced data classiﬁcation.IEEE Access, 6:70197–70211, 2018","venue":null,"work_id":"718b2fd7-3122-43b4-8899-82b2931d1368","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.343777Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:713c11bc371f2b64c3fe37470473fb6f3f078ee520893b774e52045d76de8cd2","observation_id":"cb195f25-185a-4dd2-878e-f7863d72a83d","resolution":{"observed_at":"2026-08-14T14:16:42.234884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.214743Z","title":"Bagging and boosting.Encyclopedia of Biostatistics, 1, 2005","venue":null,"work_id":"8352a450-d8d0-400d-be8f-8a9b6800b6ef","year":2005},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.348451Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:d6b5f8ba50993ea11545d82b6f7e53fed66529d31f52201b6a71a8aa2500b0e4","observation_id":"5e0287c3-66a5-415d-b365-9ca7469899b9","resolution":{"observed_at":"2026-08-14T14:16:42.219472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.200264Z","title":"An overview of ensemble methods for binary classiﬁers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes.Pattern Recognition, 44(8):1761– 1776, 2011","venue":null,"work_id":"cf459726-f19b-451b-8aab-4a3c4721fb3c","year":2011},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.353507Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:b8995a5f63865942a5c06610145afd4a183fcb961151f0271fc18d1028126dbd","observation_id":"0b254518-0aa1-4e22-be05-067bbf0966d0","resolution":{"observed_at":"2026-08-14T14:16:42.205194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.187780Z","title":"An empirical study of learning from imbalanced data using random forest","venue":null,"work_id":"9be8eb79-d8bf-4ccb-9ac2-1121837d8bb7","year":2007},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.357689Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:1a39cd2f7c6b10b544143bc4946044b7a329338dacbc6e43374d7e8d38114836","observation_id":"c1bfb602-394b-462b-8fba-b813cafe7d2c","resolution":{"observed_at":"2026-08-14T14:16:42.192211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.175071Z","title":"A novel ensemble method for imbalanced data learning: bagging of extrapolation-smote svm.Computational intelligence and neuroscience, pages 1–11, 2017","venue":null,"work_id":"b9e2dd27-9888-4b6c-bc07-ea8dfc7fdb0a","year":2017},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.361726Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:dd420f7229c738d254a094fc66cb549cbd1d8235d2e633f73d0e1dcf3fa6648a","observation_id":"b10a1be0-830d-4c6f-a144-931a13ed3c73","resolution":{"observed_at":"2026-08-14T14:16:42.179584Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.158880Z","title":"A review on ensembles for the class imbalance problem: bagging-, boosting-, and hybrid-based approaches","venue":null,"work_id":"c32173ea-327a-4632-b6d0-a28911a4428f","year":2012},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.365268Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:69a61aaf061f92f0c751aeaf098a51bb3604df613492f897ef4415b866f8de47","observation_id":"9c145dc8-d788-4819-a622-54865efae399","resolution":{"observed_at":"2026-08-14T14:16:42.163766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.144193Z","title":"A survey of multiple classiﬁer systems as hybrid systems.Information Fusion, 16:3–17, 2014","venue":null,"work_id":"d82c8008-7b42-4e76-b416-30dc6eff6909","year":2014},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.369305Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:b5551dca8564b181e13d3c0c6cd3f33acad772f0ae71b6dfc111a55f5188589a","observation_id":"0869be81-f702-45dd-ae18-4e003620d3b2","resolution":{"observed_at":"2026-08-14T14:16:42.149013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.127963Z","title":"Comparing boosting and bagging techniques with noisy and imbalanced data.IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 41(3):552–568, 2011","venue":null,"work_id":"1a0372b7-b698-4c11-a24b-2d0cef63cff3","year":2011},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.372858Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:8d0fafc9233929010b91586cb5d3d19f3c796af540386f26675178b9a44a601a","observation_id":"b8650f49-a18f-4de9-a7c2-a3131a9d41ed","resolution":{"observed_at":"2026-08-14T14:16:42.132720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.113654Z","title":"Improving classiﬁers and regions of competence in dynamic ensemble selection","venue":null,"work_id":"89508ad2-b5c5-4999-9bd9-d176fe58b142","year":2014},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.377420Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:50f752e6b480fbff0a3faf8faf796d9a01d70e65769f64b9a59d4b2205c62d31","observation_id":"6e332940-edbb-4fba-9b88-d6062eb5ca15","resolution":{"observed_at":"2026-08-14T14:16:42.118593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.099619Z","title":"Philip Kegelmeyer, and Kevin Bowyer","venue":null,"work_id":"6089473e-d3fd-4b9d-a7fa-23f8e48ee082","year":1997},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.382481Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:c73b4f8f7e03c09028651c51b3cdc794c5f5ad18f2639e2882438bd2e507f58a","observation_id":"ec720ef5-c748-47d6-b655-ff7ccf3c4a7c","resolution":{"observed_at":"2026-08-14T14:16:42.104530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.085123Z","title":"From dynamic classiﬁer selection to dynamic ensemble selection.Pattern Recognition, 41(5):1718–1731, 2008","venue":null,"work_id":"dc05c8dc-792c-4f62-b5fc-ce53f2bf82be","year":2008},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.386478Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:2f18bc2d2eecfef82b546894eb239910b8d9baf3d925acbdccd0760644a4155a","observation_id":"58dfe5f6-c810-4973-85cd-72b3a3951302","resolution":{"observed_at":"2026-08-14T14:16:42.090621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.070085Z","title":"Libd3c: ensemble classiﬁers with a clustering and dynamic selection strategy","venue":null,"work_id":"89f9070c-5688-4522-8cb0-a5542ce418fd","year":2014},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.389969Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:663cd3decbf35c134e8517877348de0eee7dab0fa4e51e4c7baedef7c64512e7","observation_id":"2cfdd2af-37f6-4b13-90a0-a925022cba79","resolution":{"observed_at":"2026-08-14T14:16:42.075303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.051890Z","title":"Meta-des: a dynamic ensemble selection framework using meta-learning.Pattern recognition, 48(5):1925– 1935, 2015","venue":null,"work_id":"e9f55d24-c599-40b2-b298-f741b152a1a6","year":1925},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.393595Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:8a3d3334b6cfbfb98b7dd75c81d8a28f1d35c1b925583f5a437eb9f517c6c345","observation_id":"12c5540a-ecbc-48ba-9ca1-88460dc3ac82","resolution":{"observed_at":"2026-08-14T14:16:42.057821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.033496Z","title":"Dynamic classiﬁer ensemble model for customer classiﬁcation with imbalanced class distribution.Expert Systems with Applications, 39(3):3668–3675, 2012","venue":null,"work_id":"8e2c7f02-d734-4cb4-b64f-8efb73f2a020","year":2012},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.397603Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:90d3c02166c5a673beeaab8c17ffd29d13cef2a93fbda1b177f659b9fdfc18dc","observation_id":"314d3d3d-dc39-4986-904b-90c066af644a","resolution":{"observed_at":"2026-08-14T14:16:42.040524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:42.016982Z","title":"Dynamic ensemble selection for multi-class classiﬁcation with one-class classiﬁers.Pattern Recognition, 83:34–51, 2018","venue":null,"work_id":"bf6b0dff-59ce-457c-985a-1332ca873f2f","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.402654Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:f7f62a0fcf538b49cada3b058e5a593ca9aa4c7af24f3d24833ba1ab4213c4a9","observation_id":"290cb5de-dd07-4b3d-9db1-3b213e497bbf","resolution":{"observed_at":"2026-08-14T14:16:42.023666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1611.06211","last_updated":"2016-11-18T19:55:29Z","snapshot_observed_at":"2026-08-14T21:29:42.664960Z","submitted_at":"2016-11-18T19:55:29Z","title":"NoiseOut: A Simple Way to Prune Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.06211","snapshot_observed_at":"2026-08-14T14:16:41.406496Z","title":"Noiseout: A simple way to prune neural networks.arXiv preprint arXiv:1611.06211, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.406496Z"},"links":{"cited_paper":"/paper/1611.06211","citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:028fa16cda15a977e53786256dd6230dd7a4b78a8aef573e29ca9f2f31ea61e8","observation_id":"5840a3a6-09e6-44e6-8181-0894cf2797e6","resolution":{"observed_at":"2026-08-14T14:16:41.406496Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.993953Z","title":"Dropout: a simple way to prevent neural networks from overﬁtting.The Journal of Machine Learning Research, 15(1):1929–1958, 2014","venue":null,"work_id":"0ddc20da-18df-463a-98ae-b5a485c3d145","year":1929},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.411487Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:93e518c125940c60cc85374d132fa7a7444f88d385d8c6b0db0570644f7b78c1","observation_id":"afc90de7-25bd-437a-a0a6-d01cb9e5855f","resolution":{"observed_at":"2026-08-14T14:16:42.002069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.415943Z","title":"Exploratory undersampling for class-imbalance learning","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.415943Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:fe08c82db323d6f39043732790ef7b0a95210c4480aa5356b866a8d54dcb69bf","observation_id":"e9dad6e5-c9da-4228-a026-eae6e7d7d0c5","resolution":{"observed_at":"2026-08-14T14:16:41.415943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.959731Z","title":"An overlap-sensitive margin classiﬁer for imbalanced and overlapping data.Expert Systems with Applications, 98:72–83, 2018","venue":null,"work_id":"c3352797-df42-4027-a361-9dd652da7280","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.420127Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:9779bb6e0c6cab87891c81b776d494bb921606218802269b494989cb5b5f29af","observation_id":"605c7ee5-585b-4c1d-9d12-e840f9a5a3d8","resolution":{"observed_at":"2026-08-14T14:16:41.965287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.940227Z","title":"Iterative regularization for learning with convex loss functions","venue":null,"work_id":"3afb2b88-c625-4161-88fc-28d0f419f7bd","year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.424047Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:b410e0ba4ac4481fec2e15efa7d6b31bb01bc9a0bca0affb3cc5b6e4eb959702","observation_id":"2d4094f4-0fbe-428f-a07f-c8746bc05ff6","resolution":{"observed_at":"2026-08-14T14:16:41.946175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.926629Z","title":"Generalization properties and im- plicit regularization for multiple passes sgm","venue":null,"work_id":"7e6f8c57-6077-4fd8-8834-3aaee44f5873","year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.428267Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:b4c3e23bc6b3ef83a14ae04fdfa5aa6992bd9b3093f4b6fd8903ebe46aa68e9f","observation_id":"636b781d-0cc6-4100-b2c5-9b1aad722f73","resolution":{"observed_at":"2026-08-14T14:16:41.930927Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.912742Z","title":"Evolutionary under- sampling boosting for imbalanced classiﬁcation of breast cancer malignancy.Applied Soft Computing, 38:714–726, 2016","venue":null,"work_id":"da2ee90c-c38e-4c36-9a86-69cd9aaa8265","year":2016},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.433084Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:1736d4e2b717acc537fa05f2b22cf97ad12e458ee1446f980a9dd19fd9a7483d","observation_id":"0c879230-23eb-49b6-9dc2-6fca29c148de","resolution":{"observed_at":"2026-08-14T14:16:41.916864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.898599Z","title":"Elblocker: Predicting blocking bugs with ensemble imbalance learning.Information and Software Technology, 61:93– 106, 2015","venue":null,"work_id":"e471e24f-cbda-42e7-86dd-ad63bf00ad6d","year":2015},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.440345Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:cd113880585ab48f6fcf2f6dae6b11c58bf0bb6b54b892afdbc7d92990c2aed6","observation_id":"4c30905d-cac5-4a74-962f-75e184ba2ef4","resolution":{"observed_at":"2026-08-14T14:16:41.903152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.883469Z","title":"Machine learning based mobile malware detection using highly imbalanced network traﬃc","venue":null,"work_id":"f0fb3143-cc53-40fd-8324-8b3c636695d1","year":2018},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.444529Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:bec826df2df8fa31b8f3cd5569747e243b72227086f0e618d18db11f442ae8ca","observation_id":"74c7a3dc-46e4-41dd-aa31-4fb109a4ae19","resolution":{"observed_at":"2026-08-14T14:16:41.889675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.865283Z","title":"A new method for occupational fraud detection in process aware information systems","venue":null,"work_id":"9e784e90-2f4a-49f1-a247-423174991b96","year":2013},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.448693Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:c2cf620935311aa6a704ecc9a7d00033199aa9191e8321a852dfadf478eb66db","observation_id":"c728daa5-8033-40e4-944b-f0afd9564189","resolution":{"observed_at":"2026-08-14T14:16:41.870783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.850252Z","title":"On convergence properties of the em algorithm for gaussian mixtures","venue":null,"work_id":"d7e51ff6-5cdd-428c-97a7-9925c923bc36","year":1996},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.452399Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:117ace5749bcad8cc278c07c4fa226095e3a7eaf807d28cda9c35f157e35aba4","observation_id":"259f3185-0dfb-420b-b36c-3ffb8b36d937","resolution":{"observed_at":"2026-08-14T14:16:41.855296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.836196Z","title":"Scikit-learn: Machine learning in python.Journal of machine learning research, 12(Oct):2825– 2830, 2011","venue":null,"work_id":"cf64db07-d7e7-4682-ad1a-71516d748389","year":2011},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.456798Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:8d895d7654826b577c7f4c85c46a22810bd1dcb726e37b0ba18f8a74b74cfbf5","observation_id":"2cbdb434-1a40-4a98-baee-423969e43610","resolution":{"observed_at":"2026-08-14T14:16:41.840947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.820271Z","title":"Sensitivity and speciﬁcity of information criteria","venue":null,"work_id":"cdec327b-17a3-4299-8710-fa756d95a1e6","year":2012},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.460523Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:6d24a32492300d4961e06b2cf2a567187562db464145634a2d5739ef9ea67a3c","observation_id":"6012d646-97da-4601-91cc-cdfa0d2fee2a","resolution":{"observed_at":"2026-08-14T14:16:41.825141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.805755Z","title":"An experiment with the edited nearest-neighbor rule.IEEE Transactions on Systems, Man, and Cybernetics, 1976","venue":null,"work_id":"b983be26-8167-455c-8be2-5c2ad253ed4b","year":1976},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.465948Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:e74b1caae932c3a06e6573480d8d379091d4f32745427780c9ca6a47afd1dcc3","observation_id":"fbe5a026-7995-430a-aa9d-7662ed2c4de2","resolution":{"observed_at":"2026-08-14T14:16:41.811302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.469966Z","title":"Friedman","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.469966Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:08cfc2c51d62fc1a520c9b0458776d57d3a097415944c0a201e4c081d349ae02","observation_id":"940204fe-8126-4eed-a173-6b6caaa100e2","resolution":{"observed_at":"2026-08-14T14:16:41.469966Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.776440Z","title":"Keel 3.0: an open source software for multi-stage analysis in data mining","venue":null,"work_id":"40b7edea-5519-42f9-afbf-d7e392ea9866","year":2017},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.475686Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:171b8a37cf67c57d3bfbad3f90e47098b3380599cd8264e9d939a92c6c3cdc6e","observation_id":"7c329605-e441-4692-a68d-5daf7a619e77","resolution":{"observed_at":"2026-08-14T14:16:41.781867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.758919Z","title":"Virtual screening of bioassay data.Journal of cheminformatics, 1(1):21, 2009","venue":null,"work_id":"bf8e5f87-20ff-4922-8063-5632dd4bb850","year":2009},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.479933Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:b44e6428eb97f78aaba238a783748dea8cee8785bc2cc50cdbf62751bb5b0ee4","observation_id":"8f82fb53-3c3e-4114-b93e-1dca44bca13b","resolution":{"observed_at":"2026-08-14T14:16:41.763713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.746002Z","title":"Espíndola and Nelson F.F","venue":null,"work_id":"708e0e5e-5a5c-4e07-ab49-e51ca5de753c","year":2005},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.485072Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:a1ed6cdd2c5b903794919366b0c240488f493dd21228ae9fc442e890c3365de0","observation_id":"0cd3cde1-bdef-4bc2-b8ec-ef61aeee3fe0","resolution":{"observed_at":"2026-08-14T14:16:41.750101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.729341Z","title":"Kernel-based extreme learning machine for remote-sensing image classiﬁcation.Remote Sensing Letters, 4(9):853–862, 2013","venue":null,"work_id":"25561971-c1cc-4fb0-be10-ffae28990d85","year":2013},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.489818Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:f50d0f556eafd8496012e3bce653e4202e13c3d548c26e582c2fa6305abe3a25","observation_id":"2947a4e8-d6a9-4b90-a334-e0738f06758b","resolution":{"observed_at":"2026-08-14T14:16:41.733872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.715104Z","title":"Individual comparisons by ranking methods","venue":null,"work_id":"749f50a0-c1cd-4526-be99-efc0e504a33d","year":1992},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.494009Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:dc4fe29c94803ccf62defb4633a7b5db725b11214595a06bf2249e135867d1a6","observation_id":"063cc4d6-47fc-4565-89fa-9b35821359ac","resolution":{"observed_at":"2026-08-14T14:16:41.719317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.700162Z","title":"Approximate statistical tests for comparing supervised classiﬁcation learning algorithms","venue":null,"work_id":"370df9e4-98b1-44af-996d-bf2d52e857eb","year":1923},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.498067Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:ae70bdbfec53a43c7b6618ae20611ca81a040930f40d7f96459c43d17322e892","observation_id":"a6795962-8caa-41ad-8bfa-4e4ef04b3bd6","resolution":{"observed_at":"2026-08-14T14:16:41.705815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.687019Z","title":"Nonparametric statistical analysis of machine learning algorithms for regression problems","venue":null,"work_id":"add1f367-3600-4ad0-ade1-1b0f75835274","year":2010},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.501843Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:4dcc92ddd49ceeb19dd3952ab1bd187b2238f53ab6eff0349a9965d3f8143dd1","observation_id":"28824647-ec30-466d-b5ae-4e8f51d7db2a","resolution":{"observed_at":"2026-08-14T14:16:41.691795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.674463Z","title":"Statsmodels: Econometric and statistical modeling with python","venue":null,"work_id":"251fc398-6209-4e05-809f-7bea77001e3f","year":2010},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.505492Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:494dcadb4f62e73943330ba852e618858d4fd087fe294f3f9bd50e6caf432903","observation_id":"a77434f9-7289-4fb0-9611-d6136bce6dc1","resolution":{"observed_at":"2026-08-14T14:16:41.678767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.661139Z","title":"Robust mixture modelling using the t distribution","venue":null,"work_id":"12e618fb-99d0-491b-b852-25c245caf286","year":2000},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.509273Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:049fa71593925461595c16e6bc757412a09e5928927df6edf957d67be13c3611","observation_id":"7ccc9786-defb-46f2-af74-675eadff3ed5","resolution":{"observed_at":"2026-08-14T14:16:41.665684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.513505Z","title":"Scalar quantization as sparse least square optimization.IEEE transactions on pattern analysis and machine intelligence, in press, DOI: 10.1109/TPAMI.2019.2952096","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.513505Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:9e557f06e150cab8e2457abae1a12b83463874fce431152d97e00fb130b36d06","observation_id":"ca73668a-f1aa-48cf-9667-a4e7db4191b9","resolution":{"observed_at":"2026-08-14T14:16:41.513505Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:16:41.645576Z","title":"Theeﬀectiveness of lloyd-type methods for the k-means problem.Journal of the ACM (JACM), 59(6):1–22, 2013","venue":null,"work_id":"2eb57a3e-1b4b-4e64-ab88-14e9ee83e514","year":2013},"citing_paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification","version":3},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-14T14:16:41.518320Z"},"links":{"citing_paper":"/paper/1908.03595"},"observation_digest":"sha256:85e9e63d7b388bbabc4bcf4d0592e64404e16d4abbabd2ed2228f10d8f189071","observation_id":"da11ee03-ac4d-4fdc-be4c-c24edd69e7eb","resolution":{"observed_at":"2026-08-14T14:16:41.651932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.03595","last_updated":"2020-11-06T00:10:02Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T04:27:45.430563Z","submitted_at":"2019-08-09T18:52:03Z","title":"Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":59},"total_outbound_references":68},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:1908.03595."}