{"as_of":"2026-08-21T08:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a184ba98b9f01c74617069f1e6aeb9f20c30da29537f62ca0e8bcf0878e62bff","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T21:44:21.524197Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2505.09279/citation-record","integrity":"/paper/2505.09279/integrity","json":"/paper/2505.09279/citation-record.json","paper":"/paper/2505.09279"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T21:44:21.326521Z","title":"A survey on distributed machine learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.326521Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:605052602ed9db9be9aa7c2f0c5c17caf3408a2ca09b116930f2f71110fd66f5","observation_id":"1fc24757-0691-4e15-9b97-c509a29b2a66","resolution":{"observed_at":"2026-08-15T21:44:21.326521Z","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":"2026-08-15T21:44:22.131132Z","title":"Modern robotics: Mechanics, planning, and control","venue":null,"work_id":"43513863-e0f5-4243-b350-17adc8b862ed","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.331304Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:f773de54f2ff593e5733df8f2c1bf2cbd5696c9a3b645261e2db556d155a9dc6","observation_id":"fa20e976-6ff0-4025-8d5b-dcf3674ffa38","resolution":{"observed_at":"2026-08-15T21:44:22.134898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.119399Z","title":"Delay effects on consensus- based distributed economic dispatch algorithm in microgrid","venue":null,"work_id":"0e504788-74b1-4d52-8f3c-f1009e5d0758","year":2017},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.335389Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:16cfe6bec9671f53c91aa26f658f42e068ae0ccb294ec9be433cf18616688d04","observation_id":"cb16bcdf-119b-4647-aa6a-4ec0e1187187","resolution":{"observed_at":"2026-08-15T21:44:22.123425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.108321Z","title":"A survey of distributed optimization","venue":null,"work_id":"645250d7-c50d-4239-829a-b707771995d5","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.339706Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:144e9510398c500725baacfd799fd3c29afb72b8ac8ef043557b7875a27c0c90","observation_id":"8d4f6fc4-d7ee-453d-9727-bb471116dd5b","resolution":{"observed_at":"2026-08-15T21:44:22.112366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.095569Z","title":"Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air","venue":null,"work_id":"4ff4b8d5-a3bf-4b2c-b848-e40dbb5ba39d","year":2020},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.343777Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:1928602ae7650cf2f62e25a17a71357420af913cc8e694d86720b5b3f0b952b2","observation_id":"58da5f2a-87cc-4430-9ec8-4581ec9b8b69","resolution":{"observed_at":"2026-08-15T21:44:22.099753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.083222Z","title":"Convergence analysis of distributed stochastic gradient descent with shuffling","venue":null,"work_id":"582a1c6e-0cf8-4951-b071-d88a0c1fe518","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.347936Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:c6477a68acdddb2e91706a3c624a882b2388922ec152d73bf8e1cf0806eb7819","observation_id":"f59309f4-d466-4f84-a224-a2ef5b8a97c2","resolution":{"observed_at":"2026-08-15T21:44:22.087428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.067078Z","title":"Distributed stochastic optimization and learning","venue":null,"work_id":"d3e64ee4-40bf-40d2-ac74-3512f2011c44","year":2014},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.351832Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:d3215e8bbb34fd6eafdd5fd14a52f870a369267757d87bae5ee1531d7a8cb6f6","observation_id":"fd1b7c86-f947-4d1b-89a5-efa003daf99c","resolution":{"observed_at":"2026-08-15T21:44:22.072166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.053444Z","title":"Distributed stochastic gradient descent with event-triggered communication","venue":null,"work_id":"3505a432-5703-4153-96c2-2149a9cb0bb4","year":2020},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.355514Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:ea5c667ae0757e12855d105fd76041a9e166f6ec735aeea10fb07c0325e84121","observation_id":"c974c6aa-2dd8-425f-9a2a-3030003d4f7a","resolution":{"observed_at":"2026-08-15T21:44:22.058047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.039367Z","title":"Distributed stochastic gradient descent: Nonconvexity, nonsmoothness, and convergence to local minima","venue":null,"work_id":"65cc9b65-6268-42c6-849b-b592b9a0f6f1","year":2022},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.359204Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:834b3f8de46328ac8ac0f0a0cbb29ce48fbb1240b1aff8c399cee94932179b23","observation_id":"851df9e2-7514-4a42-bc7f-27430c523dd2","resolution":{"observed_at":"2026-08-15T21:44:22.044308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.022874Z","title":"A sharp estimate on the transient time of distributed stochastic 10 gradient descent","venue":null,"work_id":"9252efc4-bc3f-453c-a500-c9e947cbf585","year":2021},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.362907Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:8bd8b34fd622c01c0fd1dcbb8515e236b1799f90e06e26586ec01230e732c1f2","observation_id":"34f2dd8d-a2bf-4e3c-812d-d2cdb13416d9","resolution":{"observed_at":"2026-08-15T21:44:22.027567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:22.010047Z","title":"Distributed learning in wireless networks: Recent progress and future challenges","venue":null,"work_id":"3ae8534b-e423-45a1-b685-758f4a4b3f81","year":2021},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.366915Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:f7ebc24b6b7a1bc81f933d62e1b20c4051b842f3d491b1070509da42cb5ab0c4","observation_id":"4a1172d3-a59b-487f-9c66-d5d8334b1b70","resolution":{"observed_at":"2026-08-15T21:44:22.014468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.995771Z","title":"On the linear speedup analysis of communication efficient momentum sgd for distributed non-convex optimization","venue":null,"work_id":"ce36d8a7-50dd-4520-8923-eb451827ab73","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.370517Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:ff0abc92a369bf1e1cd2b04354d52ebc320d3d13e0c4c154a2e63381401d5c29","observation_id":"ba47daf3-8d58-426d-b499-a721fca5b123","resolution":{"observed_at":"2026-08-15T21:44:22.000440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.374154Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.374154Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:d5999ab3ec402691cb8695b5ea16a1d382b966e98335a96cfcfbbba261fded7c","observation_id":"f5e6395e-6170-417c-a4b8-694516b1c578","resolution":{"observed_at":"2026-08-15T21:44:21.374154Z","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":"2026-08-15T21:44:21.975338Z","title":"A primal-dual sgd algorithm for distributed nonconvex optimization","venue":null,"work_id":"51b821bd-ca1f-4ca6-95ae-9f87dcdccf24","year":2022},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.377892Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:a4694876e27e14c392cee74585e0e9f79e8cc44f0bed01d56b6faed463daf1d1","observation_id":"2c1e8f24-efd7-4a8e-b693-a2361203bc53","resolution":{"observed_at":"2026-08-15T21:44:21.979419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.961929Z","title":"Stochastic gradient push for distributed deep learning","venue":null,"work_id":"5769a3c0-dbfc-4844-b2e7-f82f252a9760","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.381455Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:07ef76e7486b61374a240cefba8aeee315f218d5e8a00bb9105ecf0bb4c3e0c6","observation_id":"ec90ceb6-2f40-446c-8324-f4861ed8ced7","resolution":{"observed_at":"2026-08-15T21:44:21.966924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.948187Z","title":"Distributed stochastic subgradient projection algorithms for convex optimization","venue":null,"work_id":"bab829a0-937e-44df-b8c3-28151d0998c7","year":2010},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.385282Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:98775cd86ce161e708fc59c52698260cacd43f90a88d41042b1be0c2063a2f8f","observation_id":"6eae199b-5fbd-4fbe-a669-7e6dd804d632","resolution":{"observed_at":"2026-08-15T21:44:21.952582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.935794Z","title":"The heavy-tail phenomenon in sgd","venue":null,"work_id":"a5777c33-5877-4cda-aa57-35c64edbda66","year":2021},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.389251Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:e784b42dfb4880e1b06b6d892916b6bd44909bbba877c4950460022a2b2495ee","observation_id":"ef9d813e-bfb3-40a4-ab89-3cbad93ddc55","resolution":{"observed_at":"2026-08-15T21:44:21.939758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18784","last_updated":"2024-05-01T02:30:23Z","snapshot_observed_at":"2026-08-16T14:47:59.821695Z","submitted_at":"2023-10-28T18:53:41Z","title":"High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18784","snapshot_observed_at":"2026-08-15T21:44:21.392694Z","title":"High- probability convergence bounds for nonlinear stochastic gradient descent under heavy-tailed noise","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.392694Z"},"links":{"cited_paper":"/paper/2310.18784","citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:c54a9563accb16965dfdf8ba4f338c749f40ddad776a665e58885f771b7f7a7a","observation_id":"a8b48a10-f39e-44fa-9f34-58d73f8280c5","resolution":{"observed_at":"2026-08-15T21:44:21.392694Z","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":"2026-08-15T21:44:21.922900Z","title":"On proximal policy optimization’s heavy-tailed gradients","venue":null,"work_id":"bcef5f6e-6a57-451d-bc90-9f0cbaea649d","year":2021},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.397667Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:061e646109da4e036af699c047a951d8f08ed6a7936da7484aa75df1740b7d2c","observation_id":"f9847547-0f16-4e24-8870-9fc940bcbceb","resolution":{"observed_at":"2026-08-15T21:44:21.927132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.910428Z","title":"Revisiting the noise model of stochastic gradient descent","venue":null,"work_id":"325e6a6a-d85b-4da5-ae59-85bbbd5e61ef","year":2024},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.402804Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:c5c93d03ec122f315deb3c20a795f4d138873b95fc9290e04d50a423c4a28389","observation_id":"18480e0e-ec2d-48a0-9237-c63efcba3bb5","resolution":{"observed_at":"2026-08-15T21:44:21.914470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.898321Z","title":"Heavy-tail phenomenon in decentralized sgd","venue":null,"work_id":"575a4cb7-8b8d-422a-a9f9-68ad75ad87de","year":2024},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.407248Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:e8d7ae40ca194217735119ef3f9f369b38aebb01d3535fc5dd2d58a3c3808d03","observation_id":"f6421cf2-7d99-4802-be7d-c12470276d63","resolution":{"observed_at":"2026-08-15T21:44:21.902557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.411383Z","title":"Why are adaptive methods good for attention models? Advances in Neural Information Processing Systems, 33:15383–15393, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.411383Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:978b5bdff3a8b0432b568e14b45a06396b261c846dcee64cd1c8a66901ab8fe1","observation_id":"f3d8c589-8703-440b-924c-3c634b1d4b8d","resolution":{"observed_at":"2026-08-15T21:44:21.411383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.08254","last_updated":"2022-09-03T14:11:33Z","snapshot_observed_at":"2026-08-17T05:59:48.347864Z","submitted_at":"2021-06-15T16:02:37Z","title":"BEiT: BERT Pre-Training of Image Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.08254","snapshot_observed_at":"2026-08-15T21:44:21.416751Z","title":"Beit: Bert pre-training of image transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.416751Z"},"links":{"cited_paper":"/paper/2106.08254","citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:dc5802641f0837791fc8566d21074d4a5ad5e1a3dee1236595f3ef3b0357c1ff","observation_id":"5f272b2c-ab89-48a2-956d-ea3cbe70843c","resolution":{"observed_at":"2026-08-15T21:44:21.416751Z","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":"2026-08-15T21:44:21.877801Z","title":"High probability guarantees for nonconvex stochastic gradient descent with heavy tails","venue":null,"work_id":"028e1d8b-549c-4a7e-ae4b-d3c817ea0456","year":2022},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.420824Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:1116140c6a57dfd4b7547eb5bf2c3e0dd555b3ab212f6df8455f9871ba849229","observation_id":"ebb0db7c-a7ae-4ef3-bcf3-8370cbf8a9b4","resolution":{"observed_at":"2026-08-15T21:44:21.882356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.865154Z","title":"heavier-tailed","venue":null,"work_id":"0caa177d-e083-4ba2-af25-42a5c2d62be8","year":2022},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.424330Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:94e9dec789710c0eab298379f1a59e0e0fee7edab2fdc8ea4ab59564c2395ce4","observation_id":"6d543079-d17a-4b8b-84f4-9f46b238da0d","resolution":{"observed_at":"2026-08-15T21:44:21.869533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.853141Z","title":"A communication-efficient distributed gradient clipping algorithm for training deep neural networks","venue":null,"work_id":"9c4af9fa-779d-4de8-a1b5-dd86a17599b2","year":2022},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.428839Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:2fc01ac1fa3fd955ef1347a09c2ec7c197a0140ca10e91edcfe8ea2b482986b3","observation_id":"f63329dd-081d-4c37-8a0b-354cab001805","resolution":{"observed_at":"2026-08-15T21:44:21.857445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.839813Z","title":"Stochastic model- based minimization of weakly convex functions","venue":null,"work_id":"fffe2ba1-554a-45d7-9149-995f64ddd558","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.433704Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:fd3ae4f8fdaecc444db3458230d54a1cc011749cd8f2c2f9ac55beee30d02b29","observation_id":"2d6b9821-39b8-42c9-8c45-feb3bad667e4","resolution":{"observed_at":"2026-08-15T21:44:21.845453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.827647Z","title":"Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval","venue":null,"work_id":"bc3ca3d5-636b-42fd-80ed-1f8affb9a542","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.437525Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:7f24e8f88c199214766e34bb6e145629d74879568fa7ed48499a8191c76b5f94","observation_id":"9d96e557-54b4-44ad-81fb-a4bca3680b77","resolution":{"observed_at":"2026-08-15T21:44:21.831898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.814650Z","title":"First-order convergence theory for weakly-convex-weakly- concave min-max problems","venue":null,"work_id":"7fe67030-cfd7-40f6-8a8d-9c8596d48ba7","year":2021},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.441316Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:1bba92b6cf84a2b6a6fa814b374d21392a1b43b51f11a8da02bb5c2e8f206d37","observation_id":"c29a656b-2a04-4d97-9666-2cb0d612bd3a","resolution":{"observed_at":"2026-08-15T21:44:21.819283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01052","last_updated":"2024-06-15T16:44:49Z","snapshot_observed_at":"2026-08-16T14:22:19.298448Z","submitted_at":"2024-02-01T22:54:45Z","title":"Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01052","snapshot_observed_at":"2026-08-15T21:44:21.445020Z","title":"Weakly convex regularisers for inverse problems: Convergence of critical points and primal- dual optimisation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.445020Z"},"links":{"cited_paper":"/paper/2402.01052","citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:4ddfdeed67179506bc15f3c9be541220bb2b1d390cf04f0d68817e32bd6df449","observation_id":"0c5af011-e6a7-4566-8515-f2339fad6e6f","resolution":{"observed_at":"2026-08-15T21:44:21.445020Z","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":"2026-08-15T21:44:21.802276Z","title":"Delayed algorithms for distributed stochastic weakly convex optimization","venue":null,"work_id":"8e2cd1d8-e16c-4660-a8ab-a7d03bd5690e","year":2023},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.449106Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:9c49a72b44a7395a0a94f8cabe23b73795736cf2849c377a8dcbda271f2765ab","observation_id":"d104bdde-8e1f-49d6-a87f-edbddde3d79b","resolution":{"observed_at":"2026-08-15T21:44:21.806313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.789692Z","title":"On distributed nonconvex optimization: Projected subgradient method for weakly convex problems in networks","venue":null,"work_id":"449e805c-2b85-4646-b3c4-1f44bff0bcfc","year":2021},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.453203Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:e17dd8c0c6d46d70539ae601aacb4eceedc035f6683adb3bbdd7e2eb484ad341","observation_id":"0163ddcf-7426-453d-83a6-6ee21bb20ce8","resolution":{"observed_at":"2026-08-15T21:44:21.793957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15847","last_updated":"2025-05-09T01:41:45Z","snapshot_observed_at":"2026-08-16T14:31:41.193144Z","submitted_at":"2023-12-26T01:58:23Z","title":"Distributed Stochastic Optimization under Heavy-Tailed Noises","version":3},"cited_work":{"arxiv_id":"2312.15847","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.15847","snapshot_observed_at":"2026-08-15T21:44:21.589427Z","title":"Distributed Stochastic Optimization under Heavy-Tailed Noises","venue":"math.OC","work_id":"3c747614-e55c-4454-8845-522ccdf45866","year":2023},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.456842Z"},"links":{"cited_paper":"/paper/2312.15847","citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:03978cab1353413be373f57cab29aafbe44dc7f3a3873f4a581b17aa816d323e","observation_id":"8390fcc0-bc37-4698-984c-da7767dba142","resolution":{"observed_at":"2026-08-15T21:44:21.594664Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14776","last_updated":"2024-01-26T11:02:38Z","snapshot_observed_at":"2026-08-21T06:38:45.717439Z","submitted_at":"2024-01-26T11:02:38Z","title":"Online Distributed Optimization with Clipped Stochastic Gradients: High Probability Bound of Regrets","version":1},"cited_work":{"arxiv_id":"2401.14776","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.14776","snapshot_observed_at":"2026-08-15T21:44:21.567558Z","title":"Online Distributed Optimization with Clipped Stochastic Gradients: High Probability Bound of Regrets","venue":"math.OC","work_id":"4ffd6645-8ab9-4e44-89f6-9238c7c3d533","year":2024},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.460789Z"},"links":{"cited_paper":"/paper/2401.14776","citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:951366eca55bee679e3f3100ba95c088ee88c550cf8b99b1c383b578bd01ff96","observation_id":"f4f84b2c-d000-4141-ba3e-d5f9762af11c","resolution":{"observed_at":"2026-08-15T21:44:21.574716Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01860","last_updated":"2024-07-24T14:10:13Z","snapshot_observed_at":"2026-08-16T14:55:34.867740Z","submitted_at":"2023-10-03T07:49:17Z","title":"High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01860","snapshot_observed_at":"2026-08-15T21:44:21.464963Z","title":"High-probability convergence for composite and distributed stochastic minimization and variational inequalities with heavy-tailed noise","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.464963Z"},"links":{"cited_paper":"/paper/2310.01860","citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:839d28a9428a88186b029ef75d50514781a320ae1485eda3df87265d87d8232f","observation_id":"a8910fa0-f6d8-4f17-87ef-e771ce6b9862","resolution":{"observed_at":"2026-08-15T21:44:21.464963Z","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":"2026-08-15T21:44:21.777799Z","title":"Convex analysis","venue":null,"work_id":"4d1ead5e-f89f-4f82-82c4-8ae1a327761f","year":1971},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.469505Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:ffa1be1ce578609a35c0ecff5897521df02035d5fb4872d8a32edab4bd7bd838","observation_id":"a9bf99b5-1d0b-4e73-9c1f-14a750adea21","resolution":{"observed_at":"2026-08-15T21:44:21.781954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.765603Z","title":"Efficiency of minimizing compositions of convex functions and smooth maps","venue":null,"work_id":"693388c6-6c5b-422b-b69f-de6ea70c41c9","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.473785Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:2fb4475dacf19ccc252e3627d646986916ad400fe624adbce6a16011c4b53fbb","observation_id":"cc562a26-808b-4f74-8c5c-0d3a92777819","resolution":{"observed_at":"2026-08-15T21:44:21.770332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.753889Z","title":"Distributed stochastic optimization with gradient tracking over strongly-connected networks","venue":null,"work_id":"5106e3c5-f6ff-4c8a-82c2-d221331f1ecf","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.479837Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:9f00e6d9c37cd5355aba0a0d1b090ce0805554c733747dd11411104d974115dc","observation_id":"a16c7d62-f3e8-4ca4-b872-063c9a261857","resolution":{"observed_at":"2026-08-15T21:44:21.758184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.483511Z","title":"Distributed subgradient methods for multi-agent optimization","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.483511Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:136ac7ea097e9318fcc5fc98c8afcd3e0f7144de31b96e16cbacb8a0a31dd48f","observation_id":"e20cb196-2b57-4887-aa9b-44df4896b552","resolution":{"observed_at":"2026-08-15T21:44:21.483511Z","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":"2026-08-15T21:44:21.735179Z","title":"Distributed smooth convex optimization with coupled constraints","venue":null,"work_id":"5d55ff0c-2b10-4ad0-89ef-1a9693fd628f","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.487482Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:ab236a81422c5b115c6ac703111c69fdfa9b899c95d885b05317a46c34627019","observation_id":"9167adbb-88af-4d6c-8d8e-0f0418dfd4cc","resolution":{"observed_at":"2026-08-15T21:44:21.739215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.492100Z","title":"Variational analysis, volume 317","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.492100Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:5d98f874f0deeff87c63bbb36c43debc4642f5272aca4a3dda713ab459ae411e","observation_id":"52ee406f-3e7b-4119-ab7d-8bc741ee1251","resolution":{"observed_at":"2026-08-15T21:44:21.492100Z","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":"2026-08-15T21:44:21.716329Z","title":"The nonsmooth landscape of phase retrieval","venue":null,"work_id":"ce2fe7ab-2a0c-4cbd-9756-f6e35af6dc24","year":2020},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.496799Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:dc7f6f2c18e5d14c7eabb2cd4b6c4a2b486cb74e9ee2c6de4656f297aec244ce","observation_id":"879a6785-9826-4bd4-b8fa-497662e24579","resolution":{"observed_at":"2026-08-15T21:44:21.720580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.702968Z","title":"Gradient descent with random initialization: Fast global convergence for nonconvex phase retrieval","venue":null,"work_id":"bd433f27-9bca-4842-9cc5-c73caa85cfb9","year":2019},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.501538Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:633a9e6360ba82f949c1a3376bd4473c11c0a7f5948f556891c9196816c2e80d","observation_id":"926221cb-92b1-4d56-80d9-3a4036c84146","resolution":{"observed_at":"2026-08-15T21:44:21.707491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.690606Z","title":"Gradient-based learning applied to document recognition","venue":null,"work_id":"d591c378-49a7-4d5b-bfb3-92f04f36b81b","year":1998},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.506738Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:45beedbebec153335be764a82d020e6b7fd64217a53e1702ac713f3dfe0e859d","observation_id":"dfbaecb4-2838-4be9-b0f4-47867176fe63","resolution":{"observed_at":"2026-08-15T21:44:21.694897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.677374Z","title":"Heavy- tailed distributions in combinatorial search","venue":null,"work_id":"78613138-81c3-4fd4-8cca-18abf1e90316","year":1997},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.510976Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:93f087adb694093692fc2a6c19f3da1b8b9b19b8625a574750d33c2f94a342fc","observation_id":"5aed5de4-78fc-4318-aeed-bd34be52e2cd","resolution":{"observed_at":"2026-08-15T21:44:21.682067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.664304Z","title":"Proximal algorithms","venue":null,"work_id":"3eb0cba1-a54d-4575-9ba2-de2e51c84a52","year":2013},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.514875Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:2e6b377c7bb991e19a80c8566051ce2785f0585954b0dc919d15196af6280879","observation_id":"b1954a86-2d54-4513-b35c-77678bc0412d","resolution":{"observed_at":"2026-08-15T21:44:21.668702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.651999Z","title":"Convergence rate analysis of distributed optimization with projected subgradient algorithm","venue":null,"work_id":"241ddaef-7b97-44b9-926a-791f8400d7e4","year":2017},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.520125Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:fc4b0abb0991f763ace3e3ebec8598a3902023975758f1716aeac9880ec3f6e2","observation_id":"ddf85ffe-2349-42ea-8d43-4115935aaf13","resolution":{"observed_at":"2026-08-15T21:44:21.656332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T21:44:21.638554Z","title":"Constrained consensus and optimization in multi-agent networks","venue":null,"work_id":"01037b2c-e7cf-48c4-b613-f982830daf43","year":2010},"citing_paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T21:44:21.524197Z"},"links":{"citing_paper":"/paper/2505.09279"},"observation_digest":"sha256:b9e318712e6d48a0839d03d3c682567fa4afed0f676272326e23bedaee5ed8d1","observation_id":"592a5798-0c7f-43e8-823d-5a0fa7899222","resolution":{"observed_at":"2026-08-15T21:44:21.643101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.09279","last_updated":"2025-05-14T10:59:53Z","latest_version":1,"primary_category":"math.OC","snapshot_observed_at":"2026-08-18T15:11:28.279110Z","submitted_at":"2025-05-14T10:59:53Z","title":"Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":2,"verified_fuzzy":37},"total_outbound_references":48},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2505.09279."}