{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:ZPWMADFLHVBINEREBNYIUTLG3J","short_pith_number":"pith:ZPWMADFL","schema_version":"1.0","canonical_sha256":"cbecc00cab3d428692240b708a4d66da4f4c4c0d84d17f95727a90483fa1caf6","source":{"kind":"arxiv","id":"1912.04230","version":3},"attestation_state":"computed","paper":{"title":"Variance-Reduced Decentralized Stochastic Optimization with Accelerated Convergence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Ran Xin, Soummya Kar, Usman A. Khan","submitted_at":"2019-12-09T18:17:04Z","abstract_excerpt":"This paper describes a novel algorithmic framework to minimize a finite-sum of functions available over a network of nodes. The proposed framework, that we call~\\GTVR, is stochastic and decentralized, and thus is particularly suitable for problems where large-scale, potentially private data, cannot be collected or processed at a centralized server. The \\GTVR~framework leads to a family of algorithms with two key ingredients: (i) \\textit{local variance reduction}, that enables estimating the local batch gradients from arbitrarily drawn samples of local data; and, (ii) \\textit{global gradient tr"},"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":"1912.04230","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-12-09T18:17:04Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"0004d057eee7aac112d1af52425530049c0202251acbded21bb4ac99f6852aa5","abstract_canon_sha256":"ddaad3f5ac973611d3da9ed119f4ad4d0052d4c9ae00dd1ffd69cb03633bd433"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:55:44.676137Z","signature_b64":"XFZVzaAuRhaYTZ1wWqzKGh7dVCGEyk0tEH8+qd62+EkNBdC8NuCKcAFuK9OHCPuT7oaHqHvw44GCUd6KbdneAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cbecc00cab3d428692240b708a4d66da4f4c4c0d84d17f95727a90483fa1caf6","last_reissued_at":"2026-07-05T01:55:44.675724Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:55:44.675724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Variance-Reduced Decentralized Stochastic Optimization with Accelerated Convergence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Ran Xin, Soummya Kar, Usman A. Khan","submitted_at":"2019-12-09T18:17:04Z","abstract_excerpt":"This paper describes a novel algorithmic framework to minimize a finite-sum of functions available over a network of nodes. The proposed framework, that we call~\\GTVR, is stochastic and decentralized, and thus is particularly suitable for problems where large-scale, potentially private data, cannot be collected or processed at a centralized server. The \\GTVR~framework leads to a family of algorithms with two key ingredients: (i) \\textit{local variance reduction}, that enables estimating the local batch gradients from arbitrarily drawn samples of local data; and, (ii) \\textit{global gradient tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.04230","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1912.04230/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"1912.04230","created_at":"2026-07-05T01:55:44.675778+00:00"},{"alias_kind":"arxiv_version","alias_value":"1912.04230v3","created_at":"2026-07-05T01:55:44.675778+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.04230","created_at":"2026-07-05T01:55:44.675778+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZPWMADFLHVBI","created_at":"2026-07-05T01:55:44.675778+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZPWMADFLHVBINERE","created_at":"2026-07-05T01:55:44.675778+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZPWMADFL","created_at":"2026-07-05T01:55:44.675778+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/ZPWMADFLHVBINEREBNYIUTLG3J","json":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J.json","graph_json":"https://pith.science/api/pith-number/ZPWMADFLHVBINEREBNYIUTLG3J/graph.json","events_json":"https://pith.science/api/pith-number/ZPWMADFLHVBINEREBNYIUTLG3J/events.json","paper":"https://pith.science/paper/ZPWMADFL"},"agent_actions":{"view_html":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J","download_json":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J.json","view_paper":"https://pith.science/paper/ZPWMADFL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1912.04230&json=true","fetch_graph":"https://pith.science/api/pith-number/ZPWMADFLHVBINEREBNYIUTLG3J/graph.json","fetch_events":"https://pith.science/api/pith-number/ZPWMADFLHVBINEREBNYIUTLG3J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J/action/storage_attestation","attest_author":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J/action/author_attestation","sign_citation":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J/action/citation_signature","submit_replication":"https://pith.science/pith/ZPWMADFLHVBINEREBNYIUTLG3J/action/replication_record"}},"created_at":"2026-07-05T01:55:44.675778+00:00","updated_at":"2026-07-05T01:55:44.675778+00:00"}