{"as_of":"2026-08-16T13:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5ec3bb27a9f3355fadb2da7524fff968f616e58b6c617d6de6131854efbd6390","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T10:27:44.348835Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/1908.11468/citation-record","integrity":"/paper/1908.11468/integrity","json":"/paper/1908.11468/citation-record.json","paper":"/paper/1908.11468"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:27:45.003492Z","title":"Natasha: Faster non-convex stochastic optimization via strongly non- convex parameter","venue":null,"work_id":"32138f99-8469-4b4f-95a9-d8dcaf8564e8","year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.171017Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:acfafcf37848fbe262c42f7bfa3a1586be5d01dd30d1c201d832918fb643d9c3","observation_id":"54153e95-e849-402c-ad47-0c35b4ab5d22","resolution":{"observed_at":"2026-08-14T10:27:45.008663Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.988423Z","title":"Natasha 2: Faster non-convex optimization than SGD","venue":null,"work_id":"ae939acf-eaa7-4c81-8af1-b933e7557fc6","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.176438Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:ee7822d33c14a0635bffe293f57ad28505dd2d7232e1b672e0f11f6832ffdcd9","observation_id":"31fb92ac-d649-40af-8ed0-91632b4e4245","resolution":{"observed_at":"2026-08-14T10:27:44.993260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.972766Z","title":"Variance reduction for faster non-convex optimization","venue":null,"work_id":"1f9d0779-ecd3-4828-ae90-eb17eecf25fe","year":2016},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.180845Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:63cc6c77a32f1e1a033f5c9347b50fc00adfbb012a181075d6d8bc733d54ce12","observation_id":"1bb9ffa9-aa8c-400b-800a-6554887244e8","resolution":{"observed_at":"2026-08-14T10:27:44.977879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.957576Z","title":"Improved SVRG for non-strongly-convex or sum-of-non- convex objectives","venue":null,"work_id":"4aa4e973-3815-4f39-be9b-22c03f6d72d9","year":2016},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.185365Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:9538ca3b6a2748dfbce7e92a0fa9386d19a90e790e02ce50ec88f69cb1034a6b","observation_id":"b549ebe3-8a25-45c0-a147-3706bd46ca59","resolution":{"observed_at":"2026-08-14T10:27:44.962406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.189776Z","title":"First-Order Methods in Optimization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.189776Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:92fce02527fe46100782d8cccc888e88ac85ec18fe3f00acb5c41f7beb0829d0","observation_id":"2d2f9619-de81-41fc-9a19-67b4c5630417","resolution":{"observed_at":"2026-08-14T10:27:44.189776Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.07564","last_updated":"2017-11-20T21:58:01Z","snapshot_observed_at":"2026-08-14T20:11:43.806103Z","submitted_at":"2017-11-20T21:58:01Z","title":"Unbiased Simulation for Optimizing Stochastic Function Compositions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.07564","snapshot_observed_at":"2026-08-14T10:27:44.194146Z","title":"Unbiased simulation for optimizing stochastic function compositions","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.194146Z"},"links":{"cited_paper":"/paper/1711.07564","citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:04e9b9e21ceb56f462b057a61738b6d1ce9756663071a85f6a93823819339b50","observation_id":"c520e169-b92d-4f95-9862-8667ab3018d5","resolution":{"observed_at":"2026-08-14T10:27:44.194146Z","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":"2026-08-14T10:27:44.933531Z","title":"Policy evaluation with temporal dif- ferences: a survey and comparison","venue":null,"work_id":"aeb6b83a-06de-4965-b15f-191f7f6bad77","year":2014},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.199098Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:6c0c76c462b5bb4c767e03f2a7351bd11eaefa5dbadba1383f724e1ae313aa80","observation_id":"38c2e1a7-33d5-44d1-991c-1ed40cd16c8e","resolution":{"observed_at":"2026-08-14T10:27:44.937791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.920192Z","title":"SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives","venue":null,"work_id":"97033ccd-fbd6-4373-9f00-638423b98f46","year":2014},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.203025Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:0471e3d10af397e5ba7f6eba66db008fbc27bd3e1e872457405157b8505c5615","observation_id":"ccba23fa-dde5-4fb0-a088-58e89c7f684c","resolution":{"observed_at":"2026-08-14T10:27:44.924348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.906366Z","title":"Optimal distributed online prediction using mini-batches","venue":null,"work_id":"1112973c-dd35-4d1c-b183-714326635cb7","year":2012},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.206976Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:f5e6ac82b560990435c32df038d415c2e6806ce31c9260ebbbb3880678977535","observation_id":"dd029360-b753-4e94-b257-adbadfcd5697","resolution":{"observed_at":"2026-08-14T10:27:44.911073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.891806Z","title":"Statistical estimation of com- posite risk functionals and risk optimization problems","venue":null,"work_id":"e925a064-54f2-4553-ae55-b937cc777278","year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.210647Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:ccedfd642669cffd6fff3d8f7cd8b4e85f73b5c09ef55f3e68d91a26224b0770","observation_id":"c2d132c5-8ea9-4f93-a333-04a00d19e733","resolution":{"observed_at":"2026-08-14T10:27:44.896821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.877981Z","title":null,"venue":null,"work_id":"e300d779-883a-4bce-a42b-859db56f2313","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.214517Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:2f60d46feffe0c86358f2f6091ba12f0e6994d5c8eb0bc851c59d969363614fd","observation_id":"e0f9ed1a-e839-4822-a138-38d458121777","resolution":{"observed_at":"2026-08-14T10:27:44.882469Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.863599Z","title":"Ermoliev","venue":null,"work_id":"50f87632-aeb4-4953-8a67-36058e810eda","year":1976},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.218445Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:c399559a561474183f3e3909deb37da6f650cff242a9a7eace54af51b1c12a42","observation_id":"bc7344c4-6cf0-4ccf-addf-e057e9046f88","resolution":{"observed_at":"2026-08-14T10:27:44.868469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.849390Z","title":"Spider: Near-optimal non-convex optimization via stochastic path-integrated differential estimator","venue":null,"work_id":"436077fc-07b5-423e-b409-c19ecd9698a3","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.221969Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:29f01c07d70772161aef701dfe10cabcb856b6cf38c4ef1b59b01875766a4338","observation_id":"1300c7d5-82ad-4b3c-a1b3-38d6f13ced08","resolution":{"observed_at":"2026-08-14T10:27:44.854197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.835053Z","title":"Stochastic first- and zeroth-order methods for nonconvex stochastic programming","venue":null,"work_id":"e23dc128-ca39-4f80-8ce9-c9c85f6fdc3b","year":2013},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.225592Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:c8cf3acbacaa9ced60a99d35d6f6f08ff74446d8c660f2c4e585abcf64de8702","observation_id":"53a13860-1b68-47ea-bef5-c36771c8976a","resolution":{"observed_at":"2026-08-14T10:27:44.839718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1812.01094","last_updated":"2019-09-06T10:16:37Z","snapshot_observed_at":"2026-08-14T17:49:10.803688Z","submitted_at":"2018-12-03T21:58:21Z","title":"A Single Time-Scale Stochastic Approximation Method for Nested Stochastic Optimization","version":2},"cited_work":{"arxiv_id":"1812.01094","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.01094","snapshot_observed_at":"2026-08-14T10:27:44.454745Z","title":"A Single Time-Scale Stochastic Approximation Method for Nested Stochastic Optimization","venue":"math.OC","work_id":"29dc4873-ff67-4a40-953f-4be1428c5c0a","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.229152Z"},"links":{"cited_paper":"/paper/1812.01094","citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:ec1ec8bb06e9ace6b259672ad7ef3411117e52b36bc37ce291db9668131d1b4f","observation_id":"a22539c9-3ca0-493c-9ce7-d428fc3ce614","resolution":{"observed_at":"2026-08-14T10:27:44.460136Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.820635Z","title":"Accelerated method for stochastic composi- tion optimization with nonsmooth regularization","venue":null,"work_id":"33767e2a-99ce-4076-8f87-641a2f5e71d1","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.233029Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:583e435c1df7ccb8f8509c048ab5a7533c3a34e4544519b5115f187deedfd2d8","observation_id":"8def517f-c976-48a9-aea5-c78a98e11876","resolution":{"observed_at":"2026-08-14T10:27:44.825307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.806453Z","title":null,"venue":null,"work_id":"806eb578-7b7e-479a-94b8-464f87deb596","year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.236683Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:2c94c7cbb960f5cc91a4e54450851fdc8507c29c08ae6dc49755879031ebb6ae","observation_id":"ce0c7108-fc98-494e-89f9-c46b71cd82ad","resolution":{"observed_at":"2026-08-14T10:27:44.810901Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.791621Z","title":"Accelerating stochastic gradient descent using predictive vari- ance reduction","venue":null,"work_id":"46c93a62-97c9-4ec0-9a36-a1e300517209","year":2013},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.240889Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:131515e1015697b96679f1571cdef16ff5b606b5102a229c952b6fa50557e32e","observation_id":"0b621f0b-ca11-4741-9637-0ca5ee9e8b6d","resolution":{"observed_at":"2026-08-14T10:27:44.796432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.778225Z","title":"Koshal, A","venue":null,"work_id":"4e8a7424-af0f-4427-bdf6-c8ad308d55de","year":2013},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.245076Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:8674b7d695444a1d5183d9f96780b215d2bd9aa76248318090f21e2d5ef90b95","observation_id":"4cf83d3f-869e-49ab-8f96-1caa2e2f874d","resolution":{"observed_at":"2026-08-14T10:27:44.782112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.765176Z","title":"Finite-sum composition optimization via variance reduced gradient descent","venue":null,"work_id":"c826f527-5a88-4328-9dd1-2c23c1a20c28","year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.249609Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:cdb5ae6f3e25910b276b40a240e9d4aa6e9081f593bf4a0198c127270ee6d1d6","observation_id":"7cdf86db-bfd0-4baf-871f-338ba779931a","resolution":{"observed_at":"2026-08-14T10:27:44.769336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.00458","last_updated":"2020-08-29T08:32:55Z","snapshot_observed_at":"2026-08-15T14:11:10.677353Z","submitted_at":"2018-06-01T17:29:34Z","title":"Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient","version":5},"cited_work":{"arxiv_id":"1806.00458","doi":null,"metadata_source":"pith","pith_arxiv_id":"1806.00458","snapshot_observed_at":"2026-08-14T10:27:44.431697Z","title":"Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient","venue":"math.OC","work_id":"1c6ecf96-a463-4aa8-8b26-7d2619a345c3","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.254245Z"},"links":{"cited_paper":"/paper/1806.00458","citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:7c3b32939c3a46897af08afe752a39e04dca3fae80e5954133725239518ac4b1","observation_id":"fb2890a7-a5da-4928-8d1e-674e70c2e626","resolution":{"observed_at":"2026-08-14T10:27:44.438237Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.749561Z","title":"Gradient methods for minimizing composite functions","venue":null,"work_id":"9a94f87e-8c0c-41e0-a337-d45870864d66","year":2013},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.259248Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:0501b4d7519b0c98449b94cb69bc7b2b079ccde287b42553dc11aa9fbb41b349","observation_id":"0174f798-3a95-4ef2-8760-5e1dce96ece5","resolution":{"observed_at":"2026-08-14T10:27:44.755083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.734210Z","title":"Lectures on Convex Optimization","venue":null,"work_id":"ceee1b9d-e7d9-451e-b3d2-5eb0b460e3a9","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.263599Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:d943a289e38315123c0de8482ee60ec934b37d994689512fd5f15b31cbc3270c","observation_id":"206481f6-e8ee-44b5-840c-6ca68dadffbb","resolution":{"observed_at":"2026-08-14T10:27:44.738798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.719562Z","title":"Nguyen, Jie Liu, Katya Scheinberg, and Martin Tak´ aˇ c","venue":null,"work_id":"86b87621-8c5c-41bc-be21-a93dbc6635b3","year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.268096Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:5bd4b31a30fe675d3b40b336f67d0fe47cc549e7e8facefc6faba40515885409","observation_id":"fe5eafe6-01f7-4275-801c-26a008bef9bf","resolution":{"observed_at":"2026-08-14T10:27:44.724292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.07648","last_updated":"2019-04-23T03:29:01Z","snapshot_observed_at":"2026-08-14T17:27:22.206344Z","submitted_at":"2019-01-22T23:45:59Z","title":"Finite-Sum Smooth Optimization with SARAH","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.07648","snapshot_observed_at":"2026-08-14T10:27:44.272407Z","title":"Nguyen, Marten van Dijk, Dzung T","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.272407Z"},"links":{"cited_paper":"/paper/1901.07648","citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:0c44429bdaac37a09896ffd8e21cad11dfd8381ae76393bd579383422121d9a7","observation_id":"709eaa51-404f-4798-8069-51d6fc24e9c2","resolution":{"observed_at":"2026-08-14T10:27:44.272407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.05679","last_updated":"2019-03-29T03:28:35Z","snapshot_observed_at":"2026-08-14T17:16:03.467258Z","submitted_at":"2019-02-15T04:10:12Z","title":"ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.05679","snapshot_observed_at":"2026-08-14T10:27:44.277111Z","title":"Pham, Lam M","venue":null,"work_id":null,"year":1902},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.277111Z"},"links":{"cited_paper":"/paper/1902.05679","citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:34ad377ef0265a63eb2d348b33f0cbff41648fce41f939722338294da6d1ecfa","observation_id":"69704b07-3412-4757-a1fb-f4cdca8933db","resolution":{"observed_at":"2026-08-14T10:27:44.277111Z","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":"2026-08-14T10:27:44.704335Z","title":"Reddi, Ahmed Hefny, Suvrit Sra, Barnabas Poczos, and Alex Smola","venue":null,"work_id":"050f12ba-a374-4fcf-904c-8e0b8fa0359c","year":2016},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.281749Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:eec71a4a2b28a6309e0812ae12dd1b68d61e4d394abaa1c470c730f3541d2a71","observation_id":"e129a3bb-b1b1-4f06-99fb-5e3f846ff208","resolution":{"observed_at":"2026-08-14T10:27:44.709009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.689290Z","title":"Fast incremental method for smooth nonconvex optimization","venue":null,"work_id":"35700f3d-77af-49f3-bc38-6237fae75029","year":2016},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.286516Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:1f81ef05cc7a8899b76517f663577f6b12863b77653b5ce3bdcedcfc3cefdfe9","observation_id":"575da7ad-abed-4975-9116-d43357e1c15c","resolution":{"observed_at":"2026-08-14T10:27:44.694087Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.674333Z","title":"Proximal stochastic methods for nonsmooth nonconvex finite-sum optimization","venue":null,"work_id":"d8334787-95a5-448a-b223-c9770bb40cb8","year":2016},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.291046Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:20893ffeebb51b4cbb8e7ea273a4d19620f56060d2439a3edde3c09d98923940","observation_id":"b4462b89-7f2e-413d-8094-0baa23ecad39","resolution":{"observed_at":"2026-08-14T10:27:44.679134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.295485Z","title":"Tyrrell Rockafellar","venue":null,"work_id":null,"year":1970},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.295485Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:f45f6bc19f4099be390ea5260cb568678e99d132dcc0e3b9aadff5d19a412af2","observation_id":"20427cb8-f820-40fe-a846-101e9acf95c8","resolution":{"observed_at":"2026-08-14T10:27:44.295485Z","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":"2026-08-14T10:27:44.648368Z","title":"Tyrrell Rockafellar","venue":null,"work_id":"da18413c-fec7-432d-b3ba-7940882b4af1","year":2007},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.299856Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:b58214a6758504c9a6f46d04c1ee66e15fe5562628dbe34c9d09d1c01faaf013","observation_id":"15acabd7-82b5-40f3-b2ca-a8144c2be29e","resolution":{"observed_at":"2026-08-14T10:27:44.653440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.632702Z","title":"Roux, Mark Schmidt, and Francis R","venue":null,"work_id":"43b0248b-e46e-4f01-82ac-45e8018dd974","year":2012},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.304096Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:81a27e73279b3f2dec06db0273b4a7bfc4ab486d7aad9f216a29c9ca6c95005b","observation_id":"06dd9018-3862-4d5d-99e5-ab1e7ffa3e8f","resolution":{"observed_at":"2026-08-14T10:27:44.637765Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.618355Z","title":"Advances in risk-averse optimization.INFORMS TutORials in Operation Research, 2013","venue":null,"work_id":"58d9f9f7-bbcf-41fe-bf89-8cfebe8e9ea6","year":2013},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.308572Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:ec05f1cc88f612328ae81b46d5387e194fe1c2c06c913be20e4c733cc96dd02a","observation_id":"d6584bfc-2257-4228-b195-4b98a625b69e","resolution":{"observed_at":"2026-08-14T10:27:44.622953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.603343Z","title":"Reinforcement Learning: An Introduction","venue":null,"work_id":"4cef9633-fd4a-4403-9e9d-268bdb3b4d1d","year":1998},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.312923Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:4f01ad5809887571bfbc29998422b27745be3bac7e52f3e81551e527fca949c7","observation_id":"9be7ae16-6450-4dac-bcce-622bf26a0da8","resolution":{"observed_at":"2026-08-14T10:27:44.607677Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.588906Z","title":"Stochastic compositional gradient descent: algo- rithms for minimizing compositions of expected-value functions","venue":null,"work_id":"69627be7-ea4c-4c82-a9f2-06715f939a09","year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.317180Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:c10782925320fc1e5b6d76b0c2106b73c69d20a705a555f41d7b71c723ad438f","observation_id":"a45e6669-9ff8-49d9-9682-2b5f640103cb","resolution":{"observed_at":"2026-08-14T10:27:44.593318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.574930Z","title":"Accelerating stochastic composition optimization","venue":null,"work_id":"e6000316-0a84-43bc-9cd2-e4dbe79081fb","year":2017},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.321212Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:5a7ad4758f5a7af03cf96cdd2cdf3e009df5f1a29c202d1ae61181d43c72f186","observation_id":"b6a965e0-befa-424b-bc8e-6263651edb31","resolution":{"observed_at":"2026-08-14T10:27:44.579280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.10690","last_updated":"2020-05-15T19:12:01Z","snapshot_observed_at":"2026-08-14T18:09:38.867315Z","submitted_at":"2018-10-25T02:18:03Z","title":"SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.10690","snapshot_observed_at":"2026-08-14T10:27:44.325097Z","title":"SpiderBoost: A class of faster variance-reduced algorithms for nonconvex optimization","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.325097Z"},"links":{"cited_paper":"/paper/1810.10690","citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:4e246e7c3dc357758423e48dd1b5d1944a67df5bcbe47ce410aeaa5f3164a64f","observation_id":"d2713746-dec0-4c75-a474-891a3f6f132e","resolution":{"observed_at":"2026-08-14T10:27:44.325097Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:27:44.329382Z","title":"A proximal stochastic gradient method with progressive variance reduction","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.329382Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:6f407f1c10765fd9821760f57f4f3b7fa2b7f354b1e51a76c29f8bb9b17fd963","observation_id":"ae3ceb1a-7c95-49e6-a3e5-56cd356c564b","resolution":{"observed_at":"2026-08-14T10:27:44.329382Z","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":"2026-08-14T10:27:44.549788Z","title":null,"venue":null,"work_id":"f68cfa53-67c7-49a8-9a6e-7db196608bd6","year":2019},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.333253Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:b3d54d3c723f6e2d6fb4acba0f7476035ccd7eff037dee3b81392ae98904d5d5","observation_id":"d8f8b5af-bf70-47a9-b9d9-09938d65e83f","resolution":{"observed_at":"2026-08-14T10:27:44.554085Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.533659Z","title":"Adversarial examples: Attacks and defenses for deep learning","venue":null,"work_id":"adb6c90f-3447-4681-9e30-63683c95b9c2","year":2019},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.337248Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:c4504d8c7c001e0fa146e24ba6118107de6c204a0e87c5bc7ac17fd6c38339c3","observation_id":"8643c08c-67e4-48f0-80bd-5564e6f98948","resolution":{"observed_at":"2026-08-14T10:27:44.538829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.518323Z","title":"A composite randomized incremental gradient method","venue":null,"work_id":"82162ad4-8643-4cf8-9ffc-b6c02d387a02","year":2019},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.341368Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:3b943909ebe5282c0c4d6be21bb4431c171f1d14760fa1069daf3599f4a70a36","observation_id":"587f0600-d58b-42e8-b28f-aad540acf93e","resolution":{"observed_at":"2026-08-14T10:27:44.523642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.502221Z","title":"A stochastic composite gradient method with incremental variance reduction","venue":null,"work_id":"ebbe3aad-b74c-47cd-b977-c87c8fc72861","year":2019},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.345090Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:1eda88e869bd891dc2d5480f55d07698fd0877efb588df8b1ef532faf1deba67","observation_id":"2cc3c234-b457-44b1-a9dd-938b2bc73bd0","resolution":{"observed_at":"2026-08-14T10:27:44.507307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T10:27:44.486255Z","title":"Stochastic nested variance reduced gradient descent for nonconvex optimization","venue":null,"work_id":"da9bd8ce-2f76-4106-92f6-80afd695540f","year":2018},"citing_paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T10:27:44.348835Z"},"links":{"citing_paper":"/paper/1908.11468"},"observation_digest":"sha256:637b27d6fb65bce93d352207c6d52cb9865aabed0826e716b154e135a986820c","observation_id":"6fe763aa-724c-4531-afb9-ffb90282bda7","resolution":{"observed_at":"2026-08-14T10:27:44.491387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.11468","last_updated":"2021-05-10T22:58:57Z","latest_version":2,"primary_category":"math.OC","snapshot_observed_at":"2026-08-16T08:06:40.026987Z","submitted_at":"2019-08-29T22:22:06Z","title":"Multi-Level Composite Stochastic Optimization via Nested Variance Reduction"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":2,"verified_fuzzy":31},"total_outbound_references":43},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:1908.11468."}