{"as_of":"2026-08-08T14:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f25e4a763ad1903e516e26634cfb4f06b62c1fdfd2c32f41bad56c3bb3683957","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-23T06:43:37.852871Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T05:11:09.683338Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13054","snapshot_observed_at":"2026-08-03T05:11:09.683338Z","title":"HUANG, S","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.03357","last_updated":"2026-05-28T14:18:02Z","snapshot_observed_at":"2026-08-03T05:11:06.885677Z","submitted_at":"2026-02-03T10:29:34Z","title":"Achieving Linear Speedup for Composite Federated Learning","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T05:11:09.683338Z"},"links":{"cited_paper":"/paper/2412.13054","citing_paper":"/paper/2602.03357"},"observation_digest":"sha256:7c64da376c5336e9ff008cfd20ade79baa8342e3b44a93571e33f5a729cd1747","observation_id":"4fcc0887-a23d-43a5-a00c-fa3881857a02","resolution":{"observed_at":"2026-08-03T05:11:09.683338Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.13054/citation-record","integrity":"/paper/2412.13054/integrity","json":"/paper/2412.13054/citation-record.json","paper":"/paper/2412.13054"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A LGHUNAIM , K","venue":null,"work_id":"2be79008-4585-4598-bc50-7d816718183b","year":2019},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:1cd2981a4f87d65ee15788513d2d90852cff2635ad79bfa371511d1303a8ced8","observation_id":"9221ea87-87d9-4d85-9dd0-18b10a00a2b5","resolution":{"observed_at":"2026-05-23T06:45:30.464153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"3f74ba84-a715-4447-a7c9-127b6f266e64","year":2020},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:97bf30089715f0275b144aa306307c847e9f3be48d3750dba505fcb2e36fcb98","observation_id":"e625a327-d0e9-4503-82f2-34ce1fa357e5","resolution":{"observed_at":"2026-05-23T06:45:30.455031Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"0890068c-4cca-497d-b54c-4699931d01de","year":2022},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:e90c2d42978f1f2b2f2cc856aef4530735fd7bb9e726964eedc65bf5d19fd5eb","observation_id":"049ad12b-4ac8-462b-bf7c-ac071d1860a9","resolution":{"observed_at":"2026-05-23T06:45:30.460557Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"ARJEVANI , Y","venue":null,"work_id":"eb211c44-4129-4f8d-b365-974bfe766639","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:81d302bec072f19f959aa5f25be39bfcc78668500ff5bf128176de0ec49e42fa","observation_id":"f8f5d71d-b489-4694-93e1-1f7258539fcd","resolution":{"observed_at":"2026-05-23T06:45:30.427677Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"ATTOUCH , J","venue":null,"work_id":"23a6edb5-aacc-4e48-8903-3c6d9ec81f21","year":2013},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:c550d52a673b39aac8d61971011861ef0826894516b75cb40ea89f4b30034323","observation_id":"c0293b5c-a418-46b4-af5d-1d2fd825c575","resolution":{"observed_at":"2026-05-23T06:45:30.413301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"B ECK, First-order methods in optimization, SIAM","venue":null,"work_id":"7869ff19-680e-4025-8fbc-01146ea9074f","year":2017},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:1e3a4f9919be74941febaa83916fd7a59a5b59aadf537db0c7ef6f0b2a3f5b12","observation_id":"6c7617a7-376c-4a60-b5da-ff7e35442dfa","resolution":{"observed_at":"2026-05-23T06:45:30.434591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"BIANCHI AND J","venue":null,"work_id":"09aa52ef-1b0a-4bfc-a395-d49204c1208c","year":2012},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:0a613a5ecc3092241086588cc38176587fd2c4fe00a20d4b7d59e2889470a703","observation_id":"b5502494-2423-44ca-b069-97cadcf532e0","resolution":{"observed_at":"2026-05-23T06:45:30.409292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"B OTTOU , F","venue":null,"work_id":"3f680492-7f05-462b-a756-eb6d605ce027","year":2018},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:5f92e7a38be1a43fdcdd75c5f2112c969ae2659fea418e11d6219d3dddd49aeb","observation_id":"a6ea281f-9fd6-430d-b6ec-5711b5104e79","resolution":{"observed_at":"2026-05-23T06:45:30.418852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"e57258b4-d9b2-4d1a-9a4e-3eabdb436f1c","year":2012},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:373c0030fa263c958731ef59ff97d52db48a67f91b3dd85205adf7abb7116faa","observation_id":"746bb001-998b-477f-be04-3d3f43391744","resolution":{"observed_at":"2026-05-23T06:45:30.423613Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"C HIERCHIA , E","venue":null,"work_id":"04c30fba-f529-401b-8e70-5d70d8675a6d","year":2020},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:ef4214caeedc17df07a92a1ec82d36ac6fdbf510b770f4b02cc887024c691818","observation_id":"3dd54607-f591-4591-a73b-7f18716c89f9","resolution":{"observed_at":"2026-05-23T06:45:30.430964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"D AVIS AND D","venue":null,"work_id":"8461e62a-a302-484e-a8f1-707b61e5fa37","year":2019},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:44bc3e9f70604955b84455de52bfeb70d1f5e7c86161e53307906571c3b4971c","observation_id":"11c5a01e-2e88-4c2c-8df1-0fce8a0a0caf","resolution":{"observed_at":"2026-05-23T06:45:30.440107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"DI LORENZO AND G","venue":null,"work_id":"babbff30-c2c7-4dfe-b538-962c885b9fd1","year":2016},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:d95a8d3c15d33d8ac501a23320afdf93b0957fd87f63bb7c25e06b43652750b0","observation_id":"22d8de2a-1e8a-471b-a04d-0cfe79517d2d","resolution":{"observed_at":"2026-05-23T06:45:30.448996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"D RUSVYATSKIY AND A","venue":null,"work_id":"a6edafaf-a1b4-4212-afee-efe734ab740e","year":2018},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:f1757b0f6b857a175b6694cff9977a735f4ba2c0f8bfdcc6f6da12d655bd3c27","observation_id":"ab0e9570-6b9f-4d70-a395-eda8eb04702b","resolution":{"observed_at":"2026-05-23T06:45:30.387576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"E L GHECHE , G","venue":null,"work_id":"fedd42fc-cb33-4fa3-8ba5-00ecf1542c94","year":2017},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:0b201de42c19eff1a60d447e5547e120962b0d77db022c7b098b772347abb5ef","observation_id":"8f104c2a-5f57-49b8-bd38-22b50fd99f4d","resolution":{"observed_at":"2026-05-23T06:45:30.391509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"G HADIMI , G","venue":null,"work_id":"cd964922-da10-4cfe-b2f1-cd73d6e40475","year":2016},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:cb08d346630cdbe3aa49487a1a3dbb1e3387e455689cdc9440b95be500f93616","observation_id":"e481731e-42fd-4094-935e-8fc2221c226e","resolution":{"observed_at":"2026-05-23T06:45:30.395864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"c80d91a5-2760-41fa-a9c3-d733bb19b7da","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:fa02432cb1cf9e10ceb244dd46b708e526952ad8874e51087e29fd26a88ede7b","observation_id":"f73e0df9-8e72-4d98-b52e-7e82c97fb36b","resolution":{"observed_at":"2026-05-23T06:45:30.403102Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"H UANG , X","venue":null,"work_id":"8c77e8bb-251f-4908-b730-57e4ebb13c16","year":2024},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:2dffa4577e43e032e907f0003285abe2e359e684fdd6f1924f78b9e4007beca5","observation_id":"1f5a307e-3857-4b32-9fed-cd6a3cf90f6b","resolution":{"observed_at":"2026-05-23T06:45:30.379246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.05872","last_updated":"2024-09-29T03:04:49Z","snapshot_observed_at":"2026-07-06T14:41:18.044833Z","submitted_at":"2023-01-14T09:49:15Z","title":"CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence","version":3},"cited_work":{"arxiv_id":"2301.05872","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.05872","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"H UANG AND S","venue":null,"work_id":"71ead66e-d494-4ec3-bcd8-df0cb8a4ba1e","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2301.05872","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:595b32eae6675df304fa9ad62e905ec7894d825a1dfd2d74030b859446514b54","observation_id":"f4cf60c6-6581-49be-9ae7-9e016c345ff2","resolution":{"observed_at":"2026-05-23T06:45:28.331937Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.09714","last_updated":"2025-03-26T05:42:20Z","snapshot_observed_at":"2026-07-06T17:30:25.359458Z","submitted_at":"2024-02-15T05:15:22Z","title":"An Accelerated Distributed Stochastic Gradient Method with Momentum","version":3},"cited_work":{"arxiv_id":"2402.09714","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.09714","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"H UANG , S","venue":null,"work_id":"672a99f1-ad27-4995-ab22-2bc9310fa438","year":2024},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2402.09714","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:d6d60afe08f2b2e2c60b5af960ae52236377eb9f4cb132ded87cd14d2435465b","observation_id":"8487cd22-3e30-49d4-a896-dc4de9e3fced","resolution":{"observed_at":"2026-05-23T06:45:28.321449Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.12037","last_updated":"2025-03-16T07:20:57Z","snapshot_observed_at":"2026-07-06T15:44:58.275437Z","submitted_at":"2023-06-21T06:05:34Z","title":"Distributed Random Reshuffling Methods with Improved Convergence","version":3},"cited_work":{"arxiv_id":"2306.12037","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.12037","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"H UANG , L","venue":null,"work_id":"472897cb-8aea-4380-b50e-4282bacfef00","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2306.12037","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:50277d0bba04785a0c5b89d3c717c67bb002c4c97efacd0714ce810ef44e1f8f","observation_id":"7a4fe5b7-e244-4209-af8e-dab75537df98","resolution":{"observed_at":"2026-05-23T06:45:28.320183Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07100","last_updated":"2024-05-27T18:39:56Z","snapshot_observed_at":"2026-07-06T18:13:04.026351Z","submitted_at":"2024-05-11T21:58:28Z","title":"Analysis of Decentralized Stochastic Successive Convex Approximation for composite non-convex problems","version":2},"cited_work":{"arxiv_id":"2405.07100","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.07100","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"56470a5e-eef3-4712-b2c9-0f0013192d11","year":2024},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2405.07100","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:d89a1da2ceaf2b8a5cb88c058369f2b918d3c97f0292fc4c1fc062eea7db24c6","observation_id":"f0a1e303-62ed-4c4d-a804-828aac9e8203","resolution":{"observed_at":"2026-05-23T06:45:28.330856Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f09e1aa9-63e3-4cc7-ae64-4a4c20a4d073","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:b6521f575cf43d44a93ab5b6b17b5c8539d311560600c6489eff33e92b0c8202","observation_id":"8afcf3fc-519e-4e09-b6c3-0ddde30a3ec7","resolution":{"observed_at":"2026-05-23T06:45:30.375820Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"K HALED AND P","venue":null,"work_id":"70d6a1b0-0ec3-49e4-8e06-43d936ec6f07","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:fe707e9ba4cd83609c52c6cdafed9464b5b68bdbc0a399c2e25db314a9f33917","observation_id":"58479659-c8da-4dfe-ae16-ac81fbf5782d","resolution":{"observed_at":"2026-05-23T06:45:30.365427Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"L ECUN, Y","venue":null,"work_id":"ae8eb5d2-4883-4753-b9ca-891d2e3948a6","year":2015},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:df4280d459aa590c8136d132d19715d5793a5c1fbfc0e79b82e5e240260a12dc","observation_id":"38fec43f-3eb8-4fad-87e5-284e914a573b","resolution":{"observed_at":"2026-05-23T06:45:30.369676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/5.726791","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T02:06:41.659007Z","title":"Gradient-based learning applied to document recognition","venue":"Proceedings of the IEEE","work_id":"0a3595ca-57f9-43f8-8e2f-aface7154b99","year":1998},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:b44398b63baacc9350be0d29f815a1e5be04b0eb7430f037c31d8d0d806a0766","observation_id":"6c2b66ed-4e36-4f23-a2d3-100303eee36f","resolution":{"observed_at":"2026-05-23T06:45:28.160882Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-03T17:38:16.714196+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-03T17:38:16.714196+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"95d5ce9a-b19c-4710-8b91-5d92ceded1a2","year":2019},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:781ecb4ae6f38a5be1188a25e87209f91994ba1ef5db65e820099619f180d355","observation_id":"ebaf457f-20c0-43b8-abf1-5b1fd1d406a6","resolution":{"observed_at":"2026-05-23T06:45:30.361897Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"L I AND A","venue":null,"work_id":"a72ef073-ee28-4725-bd06-c67c3f163d28","year":2022},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:2c87ce694391849ad0ea42cad4278fa7cd464b3674a1254bf25723ea82ff7272","observation_id":"5c21009f-c4d8-4b1e-80da-4989402ec4e5","resolution":{"observed_at":"2026-05-23T06:45:30.356435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.01047","last_updated":"2025-07-28T03:15:32Z","snapshot_observed_at":"2026-07-06T16:55:57.634861Z","submitted_at":"2023-12-02T07:12:00Z","title":"A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization","version":3},"cited_work":{"arxiv_id":"2312.01047","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.01047","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"01566fdd-8406-47cf-984a-4c98120a191e","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2312.01047","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:26ba69b5bdf4611cd99d57054031070e32b2807ba89816ef53eb81511e8ad003","observation_id":"602e6ebc-80c0-4638-ab6a-12017bf78c09","resolution":{"observed_at":"2026-05-23T06:45:28.349713Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.04448","last_updated":"2021-08-12T16:50:52Z","snapshot_observed_at":"2026-07-06T11:37:01.608612Z","submitted_at":"2021-08-10T04:54:52Z","title":"Decentralized Composite Optimization with Compression","version":2},"cited_work":{"arxiv_id":"2108.04448","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.04448","snapshot_observed_at":"2026-07-03T08:57:47.426421Z","title":"Decentralized composite optimiza- tion with compression.arXiv preprint arXiv:2108.04448, 2021","venue":null,"work_id":"57df714b-2b86-46de-9ca2-f216fcc14197","year":2021},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2108.04448","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:98fcbed5aeb2868c57ecdb878263d044a2518f41bd23f8def2cda266c17b4b23","observation_id":"201b5af0-e92b-435a-b3cc-8fd1f49e8955","resolution":{"observed_at":"2026-05-23T06:45:28.326551Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"30333746-0f5c-4ae7-be5a-daf1c5e17e80","year":2019},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:8d370f149bc19a99dbe76fff9f48ac68584dd19ef9c83a62229a031d401d7d7b","observation_id":"9a2e7dff-c613-4829-a849-c7c3c024cd99","resolution":{"observed_at":"2026-05-23T06:45:30.382437Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"M ANCINO -BALL , S","venue":null,"work_id":"67d894e0-0864-4aaf-aacd-face24ca2fbb","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:aacbf552ebc73a709e49ac7ac1aac929be489efa2f0138022278e6d49e80bfe7","observation_id":"93ab1766-ff0b-45c9-880a-ad8ce0daf09c","resolution":{"observed_at":"2026-05-23T06:45:30.352623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2305.05828","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"M ILZAREK AND J","venue":null,"work_id":"cc1f5e2a-6853-4928-947e-e11c03c70ce4","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:46b7b237ea05994692f3d24c33779b33ba3ef80a0a5699be98172a9a10668182","observation_id":"f6426195-2e9a-46bc-bce1-2f35981de956","resolution":{"observed_at":"2026-05-23T06:45:28.325479Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1137/18m1181249","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"M ILZAREK , X","venue":"SIAM Journal on Optimization","work_id":"a31a56b7-f207-4480-93c9-5361da3eaf3f","year":2019},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:c365250ca5993da46c5b94def35a4f0261b960792192db07aabf924707dc6031","observation_id":"07b54fb5-4dfc-4766-a64e-e567df0fd1ef","resolution":{"observed_at":"2026-05-23T06:45:28.154404Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"N EDI ´C, A","venue":null,"work_id":"f5f97f6a-1e19-4e4d-8555-12e2f8a6d628","year":2018},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:715c3cd1493f1b2e73848311fc3ce4f55c7a6e8ac39eaa22eaa85de31275d69c","observation_id":"545f00b4-299b-496a-b0ad-ca28b0471e9d","resolution":{"observed_at":"2026-05-23T06:45:30.399771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"N EDI ´C, A","venue":null,"work_id":"a505136d-e0f2-4b05-a221-ea6d5067ccca","year":2017},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:40be6a3456e536f5aa8a63266f741cc62f4b0330450006da2911d5f77f57c345","observation_id":"3cc66460-ad52-4a4f-a27b-979cb54c0db9","resolution":{"observed_at":"2026-05-23T06:45:30.445124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"N EDIC AND A","venue":null,"work_id":"dc6de2d2-b23a-4292-b457-afd788e78eec","year":2009},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:088d01081aae2d67d7f3713cc492a5af31ec69c1aff2d902f1549d097a97b2b6","observation_id":"ee17e854-9f19-4b7b-bd5d-7250453aa23a","resolution":{"observed_at":"2026-05-23T06:45:30.536670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"N EDI ´C, A","venue":null,"work_id":"f593ba7c-fbbb-4f82-b542-4e6ef3c88427","year":2010},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:141611e950b6bbac3cf46a655338663d4e604afe46a795bc3dc2bd342da7040c","observation_id":"d1bdcc82-a7c8-428a-8615-52d09ca3c9ac","resolution":{"observed_at":"2026-05-23T06:45:30.544594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"O LSHEVSKY , Asymptotic network independence and step-size for a distributed subgradient method, Journal of machine learning research, 23 (2022), pp","venue":null,"work_id":"cb317b1a-7724-4dc5-b15d-430907ae90f0","year":2022},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:58c6c11b60a553c425712fc4d9cad52d4afcd177b56c710bf66116e146364437","observation_id":"6d163c72-9c76-4495-8d3d-48207d3cfa94","resolution":{"observed_at":"2026-05-23T06:45:30.548530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"O UYANG AND A","venue":null,"work_id":"c36c2e86-af79-498f-9069-5dd2fdaaaef7","year":2024},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:af7ff8a801efecdd38c8fe6405a5fa65b79b88f41214c19ac1d4e666baa05e35","observation_id":"ae439b73-3b35-4890-9b72-c210e9b838bf","resolution":{"observed_at":"2026-05-23T06:45:30.530188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"2f607346-7a15-4bbb-a138-22319ece7a6c","year":2020},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:ea3975ed34e58ec1cf0270c7ac3190d36dc091adcfe9e74e7524ac468e966999","observation_id":"4ee5c485-8deb-45f5-93e2-9c05ab1cc8ec","resolution":{"observed_at":"2026-05-23T06:45:30.511207Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"R AVAZZI, S","venue":null,"work_id":"a40af8eb-2a3f-4f64-94bd-d83f093b8264","year":2015},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:2e050f2785927e2e35c20360e7ee0530d392e4394c6d8b088a3b2180b486a5ba","observation_id":"d71c941a-8b68-4739-97c7-9c94784c4434","resolution":{"observed_at":"2026-05-23T06:45:30.501612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"197177e8-bc6b-4292-b2c7-ff416aa626f4","year":1992},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:d1b13b842db88f8ae2bc766107b23b904b8374f5a76530b92858c59daf178f0b","observation_id":"36f2e5d7-7d75-42c5-9f26-de8fee5a720b","resolution":{"observed_at":"2026-05-23T06:45:30.515312Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"59debf61-90db-45e0-a7d5-cf64ed944a1a","year":2015},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:d517c3c4724d5a43604f787879fd230820bf86aa7176f6e1a22077a294096ea5","observation_id":"614d38da-d72a-4444-9e31-a19724c56b2f","resolution":{"observed_at":"2026-05-23T06:45:30.521414Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"17f533fc-c5e1-4e97-bd8c-c9464ccef64e","year":2015},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:eba768a8fcee329f52808104b4843995e8bbdc986fd783e889c49995e8fe2d30","observation_id":"fc798a2a-5a76-499e-9564-7336a7943466","resolution":{"observed_at":"2026-05-23T06:45:30.526443Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.11573","last_updated":"2024-01-21T19:37:15Z","snapshot_observed_at":"2026-07-06T17:18:32.330256Z","submitted_at":"2024-01-21T19:37:15Z","title":"A Decentralized Proximal Gradient Tracking Algorithm for Composite Optimization on Riemannian Manifolds","version":1},"cited_work":{"arxiv_id":"2401.11573","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.11573","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"WANG , L","venue":null,"work_id":"a559b4e5-9e55-4757-88d4-15fac17f6530","year":2024},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2401.11573","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:ba83443ba5f128400db354c9b7b111a2a3804dbfbb0cd4672dab62c0a0b1221f","observation_id":"a589bb65-f41e-4e3f-a826-efb2ec5450d3","resolution":{"observed_at":"2026-05-23T06:45:28.342625Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"WANG , J","venue":null,"work_id":"cb603cdc-28e2-48a1-a0d8-20abcd564ca3","year":2021},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:fb069a8709b4dc625d2ca70637c67bee7d1fe45c11865c77689c61220a2d12e7","observation_id":"acd1de49-e510-44ed-831a-7cc645029bbb","resolution":{"observed_at":"2026-05-23T06:45:30.494791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"38fb79f1-983e-4f7a-8c70-2321f7394868","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:49072f5698681da034cc9d9e5ef801d911a28a60580e2eee0e1005ac34a131e6","observation_id":"191609ac-3fe7-4e52-a387-d82793451479","resolution":{"observed_at":"2026-05-23T06:45:30.498132Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.01594","last_updated":"2021-10-04T17:44:57Z","snapshot_observed_at":"2026-07-06T11:54:16.061506Z","submitted_at":"2021-10-04T17:44:57Z","title":"A Stochastic Proximal Gradient Framework for Decentralized Non-Convex Composite Optimization: Topology-Independent Sample Complexity and Communication Efficiency","version":1},"cited_work":{"arxiv_id":"2110.01594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.01594","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A stochastic proximal gradient framework for decentralized non-convex composite optimiza- tion: Topology-independent sample complexity and communication ef- ficiency","venue":null,"work_id":"0603aa66-7474-43cf-b13f-d7be432b1d8e","year":2021},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"cited_paper":"/paper/2110.01594","citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:43b6212093030178da9249df4da57891f69eb5d0ce030574d043277817be8d34","observation_id":"0b7817ce-fd4d-4d94-9c15-522a19b5b09b","resolution":{"observed_at":"2026-05-23T06:45:28.337077Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"1071c254-5840-44aa-8ffc-7cca6cd24fbd","year":2021},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:b096849102f96c7701bf3ac3be851d65c1106ec357bebf00e341fca322fd1a29","observation_id":"a974938b-3a5e-407f-880c-a1f38b05a37c","resolution":{"observed_at":"2026-05-23T06:45:30.541193Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"9f016cf7-a74e-4b34-ae27-8b0a640a6011","year":2015},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:b2c219bbd74488b6fbd65816df0a8a90d1eb34b15761af0414fb4fdfc8f896ee","observation_id":"1dfba715-42bd-4c91-882d-e1f39a75c348","resolution":{"observed_at":"2026-05-23T06:45:30.484404Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"4a878f02-7a51-4c67-a0cf-2b2f4fe2ca29","year":2023},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:9fe165c73a505fc14dbf8a677101f4e0c49ce5957dc26f5dcd9a2299b9fc6ae3","observation_id":"43631fd1-2742-478d-9eaa-779ebc15c5ed","resolution":{"observed_at":"2026-05-23T06:45:30.478672Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"a66bc1e9-7b3d-40e1-b70a-6a0dd6db16fb","year":2020},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:f138ba77a5195cd9a2e4ea310d923c345e536cd1bb12de783b053f9cdece737c","observation_id":"240a86c5-2252-49db-a2c9-f27e6eea0de5","resolution":{"observed_at":"2026-05-23T06:45:30.490622Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"Y UAN, B","venue":null,"work_id":"db511cf1-339d-48f1-957e-4ae9445cfe44","year":2018},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:1500415aed188d6adf8a26a57e1d82a6d8f409e20b120eb730a9917b69d19745","observation_id":"f4b9ac97-af36-4c22-a216-787d5d7ee3d2","resolution":{"observed_at":"2026-05-23T06:45:30.475173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"Z ENG AND W","venue":null,"work_id":"ad3e734f-6eba-49fc-96e6-8805c1251c02","year":2018},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:5a0842b86eef4255f6c71e5d90e4909e2810962cbaf95be1f3d96cf685c5d51a","observation_id":"9e736ce2-dc69-451f-869b-1e587a193c6d","resolution":{"observed_at":"2026-05-23T06:45:30.470669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-06-05T21:23:00.469572Z","title":"Z OU AND T","venue":null,"work_id":"c1b13ed6-d1d8-4343-8817-8cf1960f5719","year":2005},"citing_paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-23T06:43:37.852871Z"},"links":{"citing_paper":"/paper/2412.13054"},"observation_digest":"sha256:3e22ae4175d8517d81e2d4e0a53894974cb581626c4631c541db6acb6ed3e0c5","observation_id":"09065c5e-fabb-4738-8c73-744ed7c7ddc9","resolution":{"observed_at":"2026-05-23T06:45:30.467416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.13054","last_updated":"2026-05-03T09:49:41Z","latest_version":3,"primary_category":"math.OC","snapshot_observed_at":"2026-07-06T20:08:38.939649Z","submitted_at":"2024-12-17T16:15:42Z","title":"Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":11,"verified_fuzzy":28},"total_outbound_references":55},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2412.13054."}