{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:QVL3RA5P7OUBPPO5GIFYMQDYGT","short_pith_number":"pith:QVL3RA5P","schema_version":"1.0","canonical_sha256":"8557b883affba817bddd320b86407834ea7a3008214a1250fd5b1e1f6e1d68cb","source":{"kind":"arxiv","id":"1808.05156","version":1},"attestation_state":"computed","paper":{"title":"An Analysis of Asynchronous Stochastic Accelerated Coordinate Descent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"math.OC","authors_text":"Richard Cole, Yixin Tao","submitted_at":"2018-08-15T15:46:56Z","abstract_excerpt":"Gradient descent, and coordinate descent in particular, are core tools in machine learning and elsewhere. Large problem instances are common. To help solve them, two orthogonal approaches are known: acceleration and parallelism. In this work, we ask whether they can be used simultaneously. The answer is \"yes\".\n  More specifically, we consider an asynchronous parallel version of the accelerated coordinate descent algorithm proposed and analyzed by Lin, Liu and Xiao (SIOPT'15). We give an analysis based on the efficient implementation of this algorithm. The only constraint is a standard bounded "},"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":"1808.05156","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-08-15T15:46:56Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"30c5348ceca612bbf400bdf54b800f44059075649b43a1a2dd05aabc7e3c175e","abstract_canon_sha256":"1fe2210713b7bb783688b2b6537d2f6889691b6f50c634269c2a5aec78eace29"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:01.455722Z","signature_b64":"tOz4iiwZBRwU4c5LNQDsFVzMp/Igss1erG4GDWZoHHqSQ02CSrnWlacapv2vwLeeSNKkSmRnyceBc3mvUcNLDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8557b883affba817bddd320b86407834ea7a3008214a1250fd5b1e1f6e1d68cb","last_reissued_at":"2026-05-18T00:08:01.455155Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:01.455155Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Analysis of Asynchronous Stochastic Accelerated Coordinate Descent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"math.OC","authors_text":"Richard Cole, Yixin Tao","submitted_at":"2018-08-15T15:46:56Z","abstract_excerpt":"Gradient descent, and coordinate descent in particular, are core tools in machine learning and elsewhere. Large problem instances are common. To help solve them, two orthogonal approaches are known: acceleration and parallelism. In this work, we ask whether they can be used simultaneously. The answer is \"yes\".\n  More specifically, we consider an asynchronous parallel version of the accelerated coordinate descent algorithm proposed and analyzed by Lin, Liu and Xiao (SIOPT'15). We give an analysis based on the efficient implementation of this algorithm. The only constraint is a standard bounded "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.05156","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":"1808.05156","created_at":"2026-05-18T00:08:01.455255+00:00"},{"alias_kind":"arxiv_version","alias_value":"1808.05156v1","created_at":"2026-05-18T00:08:01.455255+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.05156","created_at":"2026-05-18T00:08:01.455255+00:00"},{"alias_kind":"pith_short_12","alias_value":"QVL3RA5P7OUB","created_at":"2026-05-18T12:32:46.962924+00:00"},{"alias_kind":"pith_short_16","alias_value":"QVL3RA5P7OUBPPO5","created_at":"2026-05-18T12:32:46.962924+00:00"},{"alias_kind":"pith_short_8","alias_value":"QVL3RA5P","created_at":"2026-05-18T12:32:46.962924+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/QVL3RA5P7OUBPPO5GIFYMQDYGT","json":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT.json","graph_json":"https://pith.science/api/pith-number/QVL3RA5P7OUBPPO5GIFYMQDYGT/graph.json","events_json":"https://pith.science/api/pith-number/QVL3RA5P7OUBPPO5GIFYMQDYGT/events.json","paper":"https://pith.science/paper/QVL3RA5P"},"agent_actions":{"view_html":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT","download_json":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT.json","view_paper":"https://pith.science/paper/QVL3RA5P","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1808.05156&json=true","fetch_graph":"https://pith.science/api/pith-number/QVL3RA5P7OUBPPO5GIFYMQDYGT/graph.json","fetch_events":"https://pith.science/api/pith-number/QVL3RA5P7OUBPPO5GIFYMQDYGT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT/action/storage_attestation","attest_author":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT/action/author_attestation","sign_citation":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT/action/citation_signature","submit_replication":"https://pith.science/pith/QVL3RA5P7OUBPPO5GIFYMQDYGT/action/replication_record"}},"created_at":"2026-05-18T00:08:01.455255+00:00","updated_at":"2026-05-18T00:08:01.455255+00:00"}