{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:3M5UVTK72WKBEGU3VUGP6BVZVS","short_pith_number":"pith:3M5UVTK7","schema_version":"1.0","canonical_sha256":"db3b4acd5fd594121a9bad0cff06b9aca6665e8d7bfc0a38e43a56206f53f0a9","source":{"kind":"arxiv","id":"1405.0782","version":2},"attestation_state":"computed","paper":{"title":"Optimality guarantees for distributed statistical estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","math.IT","math.ST","stat.TH"],"primary_cat":"cs.IT","authors_text":"John C. Duchi, Martin J. Wainwright, Michael I. Jordan, Yuchen Zhang","submitted_at":"2014-05-05T05:23:30Z","abstract_excerpt":"Large data sets often require performing distributed statistical estimation, with a full data set split across multiple machines and limited communication between machines. To study such scenarios, we define and study some refinements of the classical minimax risk that apply to distributed settings, comparing to the performance of estimators with access to the entire data. Lower bounds on these quantities provide a precise characterization of the minimum amount of communication required to achieve the centralized minimax risk. We study two classes of distributed protocols: one in which machine"},"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":"1405.0782","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2014-05-05T05:23:30Z","cross_cats_sorted":["cs.LG","math.IT","math.ST","stat.TH"],"title_canon_sha256":"3d24d2ff769a70b0fc3ce091c1af07ebbcb892873502171edd3268135dbdb4a3","abstract_canon_sha256":"4d86afd1024e05a0cdb98b28ef615c28a56adc40492b2c5007b56d7d31cc3f29"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:49:11.634456Z","signature_b64":"eGCM/STav0aZmlk/kJNkj6fdKmV+/iavmuet3d/RUkHzVFbfvjlmg3W/qQXwTBzVxv4Do61F9l37TaVlsySJBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db3b4acd5fd594121a9bad0cff06b9aca6665e8d7bfc0a38e43a56206f53f0a9","last_reissued_at":"2026-05-18T02:49:11.633860Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:49:11.633860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimality guarantees for distributed statistical estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","math.IT","math.ST","stat.TH"],"primary_cat":"cs.IT","authors_text":"John C. Duchi, Martin J. Wainwright, Michael I. Jordan, Yuchen Zhang","submitted_at":"2014-05-05T05:23:30Z","abstract_excerpt":"Large data sets often require performing distributed statistical estimation, with a full data set split across multiple machines and limited communication between machines. To study such scenarios, we define and study some refinements of the classical minimax risk that apply to distributed settings, comparing to the performance of estimators with access to the entire data. Lower bounds on these quantities provide a precise characterization of the minimum amount of communication required to achieve the centralized minimax risk. We study two classes of distributed protocols: one in which machine"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1405.0782","kind":"arxiv","version":2},"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":"1405.0782","created_at":"2026-05-18T02:49:11.633946+00:00"},{"alias_kind":"arxiv_version","alias_value":"1405.0782v2","created_at":"2026-05-18T02:49:11.633946+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1405.0782","created_at":"2026-05-18T02:49:11.633946+00:00"},{"alias_kind":"pith_short_12","alias_value":"3M5UVTK72WKB","created_at":"2026-05-18T12:28:11.866339+00:00"},{"alias_kind":"pith_short_16","alias_value":"3M5UVTK72WKBEGU3","created_at":"2026-05-18T12:28:11.866339+00:00"},{"alias_kind":"pith_short_8","alias_value":"3M5UVTK7","created_at":"2026-05-18T12:28:11.866339+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/3M5UVTK72WKBEGU3VUGP6BVZVS","json":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS.json","graph_json":"https://pith.science/api/pith-number/3M5UVTK72WKBEGU3VUGP6BVZVS/graph.json","events_json":"https://pith.science/api/pith-number/3M5UVTK72WKBEGU3VUGP6BVZVS/events.json","paper":"https://pith.science/paper/3M5UVTK7"},"agent_actions":{"view_html":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS","download_json":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS.json","view_paper":"https://pith.science/paper/3M5UVTK7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1405.0782&json=true","fetch_graph":"https://pith.science/api/pith-number/3M5UVTK72WKBEGU3VUGP6BVZVS/graph.json","fetch_events":"https://pith.science/api/pith-number/3M5UVTK72WKBEGU3VUGP6BVZVS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS/action/storage_attestation","attest_author":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS/action/author_attestation","sign_citation":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS/action/citation_signature","submit_replication":"https://pith.science/pith/3M5UVTK72WKBEGU3VUGP6BVZVS/action/replication_record"}},"created_at":"2026-05-18T02:49:11.633946+00:00","updated_at":"2026-05-18T02:49:11.633946+00:00"}