{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:MYH2YJSWOAZRWIZXRNUR4BROSH","short_pith_number":"pith:MYH2YJSW","schema_version":"1.0","canonical_sha256":"660fac265670331b23378b691e062e91e88249a3caf4c3e7a7c42acd237e066b","source":{"kind":"arxiv","id":"1902.04774","version":1},"attestation_state":"computed","paper":{"title":"Distributed Online Linear Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","math.OC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Alexandre Proutiere, Deming Yuan, Guodong Shi","submitted_at":"2019-02-13T07:37:03Z","abstract_excerpt":"We study online linear regression problems in a distributed setting, where the data is spread over a network. In each round, each network node proposes a linear predictor, with the objective of fitting the \\emph{network-wide} data. It then updates its predictor for the next round according to the received local feedback and information received from neighboring nodes. The predictions made at a given node are assessed through the notion of regret, defined as the difference between their cumulative network-wide square errors and those of the best off-line network-wide linear predictor. Various s"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1902.04774","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-13T07:37:03Z","cross_cats_sorted":["cs.DC","math.OC","stat.ML"],"title_canon_sha256":"6ebfb14e3306318560caeff18c8ff6e247fda99741a11d74619604b292143577","abstract_canon_sha256":"17190771824011d8e14226b8a8bcb6f5591180f8c21ee1d903b583bbf2884b42"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:05.978749Z","signature_b64":"oFUwx21B8qzjhICnyMkzNu42JOC+gxd7zJxYhyBj8gbxA1DabqKC5c+dWXWvWcg+vPs5suDGK6ZbbkRHXvDgAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"660fac265670331b23378b691e062e91e88249a3caf4c3e7a7c42acd237e066b","last_reissued_at":"2026-05-17T23:54:05.978280Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:05.978280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributed Online Linear Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","math.OC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Alexandre Proutiere, Deming Yuan, Guodong Shi","submitted_at":"2019-02-13T07:37:03Z","abstract_excerpt":"We study online linear regression problems in a distributed setting, where the data is spread over a network. In each round, each network node proposes a linear predictor, with the objective of fitting the \\emph{network-wide} data. It then updates its predictor for the next round according to the received local feedback and information received from neighboring nodes. The predictions made at a given node are assessed through the notion of regret, defined as the difference between their cumulative network-wide square errors and those of the best off-line network-wide linear predictor. Various s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.04774","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1902.04774","created_at":"2026-05-17T23:54:05.978359+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.04774v1","created_at":"2026-05-17T23:54:05.978359+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.04774","created_at":"2026-05-17T23:54:05.978359+00:00"},{"alias_kind":"pith_short_12","alias_value":"MYH2YJSWOAZR","created_at":"2026-05-18T12:33:24.271573+00:00"},{"alias_kind":"pith_short_16","alias_value":"MYH2YJSWOAZRWIZX","created_at":"2026-05-18T12:33:24.271573+00:00"},{"alias_kind":"pith_short_8","alias_value":"MYH2YJSW","created_at":"2026-05-18T12:33:24.271573+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH","json":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH.json","graph_json":"https://pith.science/api/pith-number/MYH2YJSWOAZRWIZXRNUR4BROSH/graph.json","events_json":"https://pith.science/api/pith-number/MYH2YJSWOAZRWIZXRNUR4BROSH/events.json","paper":"https://pith.science/paper/MYH2YJSW"},"agent_actions":{"view_html":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH","download_json":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH.json","view_paper":"https://pith.science/paper/MYH2YJSW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.04774&json=true","fetch_graph":"https://pith.science/api/pith-number/MYH2YJSWOAZRWIZXRNUR4BROSH/graph.json","fetch_events":"https://pith.science/api/pith-number/MYH2YJSWOAZRWIZXRNUR4BROSH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH/action/storage_attestation","attest_author":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH/action/author_attestation","sign_citation":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH/action/citation_signature","submit_replication":"https://pith.science/pith/MYH2YJSWOAZRWIZXRNUR4BROSH/action/replication_record"}},"created_at":"2026-05-17T23:54:05.978359+00:00","updated_at":"2026-05-17T23:54:05.978359+00:00"}