{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:RMG3KKKAIZWJB6MQEDLSGCYHSX","short_pith_number":"pith:RMG3KKKA","schema_version":"1.0","canonical_sha256":"8b0db52940466c90f99020d7230b0795eac09b28295a96869c7fb29968c23612","source":{"kind":"arxiv","id":"1109.4960","version":2},"attestation_state":"computed","paper":{"title":"Distributed Linear Parameter Estimation: Asymptotically Efficient Adaptive Strategies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","math.PR","math.ST","stat.TH"],"primary_cat":"math.OC","authors_text":"H. Vincent Poor, Jose' M. F. Moura, Soummya Kar","submitted_at":"2011-09-22T21:54:18Z","abstract_excerpt":"The paper considers the problem of distributed adaptive linear parameter estimation in multi-agent inference networks. Local sensing model information is only partially available at the agents and inter-agent communication is assumed to be unpredictable. The paper develops a generic mixed time-scale stochastic procedure consisting of simultaneous distributed learning and estimation, in which the agents adaptively assess their relative observation quality over time and fuse the innovations accordingly. Under rather weak assumptions on the statistical model and the inter-agent communication, it "},"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":"1109.4960","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2011-09-22T21:54:18Z","cross_cats_sorted":["cs.SY","math.PR","math.ST","stat.TH"],"title_canon_sha256":"9f2a92945c6c7d26ed7e1825ecb5f2f8524dca6c60fe411af0f3f4a9b8ae243b","abstract_canon_sha256":"4ccede13b5205f8e7bb5d5f022247bdad7abf5b346793f359772123fdc79c264"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:49:22.208906Z","signature_b64":"VVOJY2abIe5lPcP9PquCDPFjTFySzgZj3NsCApwYxIcCDbe4UU95VW9lEl+a8Kh1uTtAOS4hOtgdBrpCSOQrCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b0db52940466c90f99020d7230b0795eac09b28295a96869c7fb29968c23612","last_reissued_at":"2026-05-18T03:49:22.207989Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:49:22.207989Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributed Linear Parameter Estimation: Asymptotically Efficient Adaptive Strategies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","math.PR","math.ST","stat.TH"],"primary_cat":"math.OC","authors_text":"H. Vincent Poor, Jose' M. F. Moura, Soummya Kar","submitted_at":"2011-09-22T21:54:18Z","abstract_excerpt":"The paper considers the problem of distributed adaptive linear parameter estimation in multi-agent inference networks. Local sensing model information is only partially available at the agents and inter-agent communication is assumed to be unpredictable. The paper develops a generic mixed time-scale stochastic procedure consisting of simultaneous distributed learning and estimation, in which the agents adaptively assess their relative observation quality over time and fuse the innovations accordingly. Under rather weak assumptions on the statistical model and the inter-agent communication, it "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1109.4960","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":"1109.4960","created_at":"2026-05-18T03:49:22.208144+00:00"},{"alias_kind":"arxiv_version","alias_value":"1109.4960v2","created_at":"2026-05-18T03:49:22.208144+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1109.4960","created_at":"2026-05-18T03:49:22.208144+00:00"},{"alias_kind":"pith_short_12","alias_value":"RMG3KKKAIZWJ","created_at":"2026-05-18T12:26:41.206345+00:00"},{"alias_kind":"pith_short_16","alias_value":"RMG3KKKAIZWJB6MQ","created_at":"2026-05-18T12:26:41.206345+00:00"},{"alias_kind":"pith_short_8","alias_value":"RMG3KKKA","created_at":"2026-05-18T12:26:41.206345+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/RMG3KKKAIZWJB6MQEDLSGCYHSX","json":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX.json","graph_json":"https://pith.science/api/pith-number/RMG3KKKAIZWJB6MQEDLSGCYHSX/graph.json","events_json":"https://pith.science/api/pith-number/RMG3KKKAIZWJB6MQEDLSGCYHSX/events.json","paper":"https://pith.science/paper/RMG3KKKA"},"agent_actions":{"view_html":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX","download_json":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX.json","view_paper":"https://pith.science/paper/RMG3KKKA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1109.4960&json=true","fetch_graph":"https://pith.science/api/pith-number/RMG3KKKAIZWJB6MQEDLSGCYHSX/graph.json","fetch_events":"https://pith.science/api/pith-number/RMG3KKKAIZWJB6MQEDLSGCYHSX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX/action/storage_attestation","attest_author":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX/action/author_attestation","sign_citation":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX/action/citation_signature","submit_replication":"https://pith.science/pith/RMG3KKKAIZWJB6MQEDLSGCYHSX/action/replication_record"}},"created_at":"2026-05-18T03:49:22.208144+00:00","updated_at":"2026-05-18T03:49:22.208144+00:00"}