{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:OGWWXNKPGZ4JPJYT3H3JYLS3ZA","short_pith_number":"pith:OGWWXNKP","schema_version":"1.0","canonical_sha256":"71ad6bb54f367897a713d9f69c2e5bc83155d6d54f047013abe815b76d494e71","source":{"kind":"arxiv","id":"2502.17615","version":1},"attestation_state":"computed","paper":{"title":"Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DC","math.OC"],"primary_cat":"cs.LG","authors_text":"Anastasios Kyrillidis, Fangshuo Liao, Wenyi Su","submitted_at":"2025-02-24T20:02:27Z","abstract_excerpt":"We study a distributed Principal Component Analysis (PCA) framework where each worker targets a distinct eigenvector and refines its solution by updating from intermediate solutions provided by peers deemed as \"superior\". Drawing intuition from the deflation method in centralized eigenvalue problems, our approach breaks the sequential dependency in the deflation steps and allows asynchronous updates of workers, while incurring only a small communication cost. To our knowledge, a gap in the literature -- the theoretical underpinning of such distributed, dynamic interactions among workers -- has"},"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":"2502.17615","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-24T20:02:27Z","cross_cats_sorted":["cs.DC","math.OC"],"title_canon_sha256":"737e7ac76f89ddf6d0da7a985e1862b564feb775c1552cc01c1ae5a0d6610c7b","abstract_canon_sha256":"9cb9cec8f654a09d8699aa4ddcfdf6bf5450ada31f69d3401634a5738120fe65"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:20:20.642362Z","signature_b64":"z4Q95WGM7GeBi2F9moPHxeYrpPphUUXaPhnr2I9M4s7ChSK+SuVmbwRX0FlBXiL07WeCFL6CrGaCbAcOe3RlAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71ad6bb54f367897a713d9f69c2e5bc83155d6d54f047013abe815b76d494e71","last_reissued_at":"2026-07-05T10:20:20.641763Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:20:20.641763Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DC","math.OC"],"primary_cat":"cs.LG","authors_text":"Anastasios Kyrillidis, Fangshuo Liao, Wenyi Su","submitted_at":"2025-02-24T20:02:27Z","abstract_excerpt":"We study a distributed Principal Component Analysis (PCA) framework where each worker targets a distinct eigenvector and refines its solution by updating from intermediate solutions provided by peers deemed as \"superior\". Drawing intuition from the deflation method in centralized eigenvalue problems, our approach breaks the sequential dependency in the deflation steps and allows asynchronous updates of workers, while incurring only a small communication cost. To our knowledge, a gap in the literature -- the theoretical underpinning of such distributed, dynamic interactions among workers -- has"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.17615","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2502.17615/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":"2502.17615","created_at":"2026-07-05T10:20:20.641848+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.17615v1","created_at":"2026-07-05T10:20:20.641848+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.17615","created_at":"2026-07-05T10:20:20.641848+00:00"},{"alias_kind":"pith_short_12","alias_value":"OGWWXNKPGZ4J","created_at":"2026-07-05T10:20:20.641848+00:00"},{"alias_kind":"pith_short_16","alias_value":"OGWWXNKPGZ4JPJYT","created_at":"2026-07-05T10:20:20.641848+00:00"},{"alias_kind":"pith_short_8","alias_value":"OGWWXNKP","created_at":"2026-07-05T10:20:20.641848+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/OGWWXNKPGZ4JPJYT3H3JYLS3ZA","json":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA.json","graph_json":"https://pith.science/api/pith-number/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/graph.json","events_json":"https://pith.science/api/pith-number/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/events.json","paper":"https://pith.science/paper/OGWWXNKP"},"agent_actions":{"view_html":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA","download_json":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA.json","view_paper":"https://pith.science/paper/OGWWXNKP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.17615&json=true","fetch_graph":"https://pith.science/api/pith-number/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/graph.json","fetch_events":"https://pith.science/api/pith-number/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/action/storage_attestation","attest_author":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/action/author_attestation","sign_citation":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/action/citation_signature","submit_replication":"https://pith.science/pith/OGWWXNKPGZ4JPJYT3H3JYLS3ZA/action/replication_record"}},"created_at":"2026-07-05T10:20:20.641848+00:00","updated_at":"2026-07-05T10:20:20.641848+00:00"}