{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:3ZA3T4JJ5SZ27FJMZ4D3LWXGFD","short_pith_number":"pith:3ZA3T4JJ","schema_version":"1.0","canonical_sha256":"de41b9f129ecb3af952ccf07b5dae628c69fc1991ba1b950699dca81f13c70d4","source":{"kind":"arxiv","id":"1511.01509","version":1},"attestation_state":"computed","paper":{"title":"Newton-Raphson Consensus for Distributed Convex Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Angelo Cenedese, Damiano Varagnolo, Filippo Zanella, Gianluigi Pillonetto, Luca Schenato","submitted_at":"2015-11-04T21:04:58Z","abstract_excerpt":"We address the problem of distributed uncon- strained convex optimization under separability assumptions, i.e., the framework where each agent of a network is endowed with a local private multidimensional convex cost, is subject to communication constraints, and wants to collaborate to compute the minimizer of the sum of the local costs. We propose a design methodology that combines average consensus algorithms and separation of time-scales ideas. This strategy is proved, under suitable hypotheses, to be globally convergent to the true minimizer. Intuitively, the procedure lets the agents dist"},"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":"1511.01509","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2015-11-04T21:04:58Z","cross_cats_sorted":[],"title_canon_sha256":"5a644521093c3c9c6ba89716d9755d5be7647f6bb943a68d5c21905acfd0f737","abstract_canon_sha256":"57687eaf72b77ce2bde03cbceecd58f118ce5da5dbe4db0a379afe9f46c58945"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:27:45.401587Z","signature_b64":"svsmPShaoYIpU244aDANBtpps+oL8HZCSWXXG2LbvhEW/OFJZcx86FepXMxCG6uxFKTa164V1g3/rTchSUXGBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"de41b9f129ecb3af952ccf07b5dae628c69fc1991ba1b950699dca81f13c70d4","last_reissued_at":"2026-05-18T01:27:45.400932Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:27:45.400932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Newton-Raphson Consensus for Distributed Convex Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Angelo Cenedese, Damiano Varagnolo, Filippo Zanella, Gianluigi Pillonetto, Luca Schenato","submitted_at":"2015-11-04T21:04:58Z","abstract_excerpt":"We address the problem of distributed uncon- strained convex optimization under separability assumptions, i.e., the framework where each agent of a network is endowed with a local private multidimensional convex cost, is subject to communication constraints, and wants to collaborate to compute the minimizer of the sum of the local costs. We propose a design methodology that combines average consensus algorithms and separation of time-scales ideas. This strategy is proved, under suitable hypotheses, to be globally convergent to the true minimizer. Intuitively, the procedure lets the agents dist"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.01509","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":"1511.01509","created_at":"2026-05-18T01:27:45.401025+00:00"},{"alias_kind":"arxiv_version","alias_value":"1511.01509v1","created_at":"2026-05-18T01:27:45.401025+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.01509","created_at":"2026-05-18T01:27:45.401025+00:00"},{"alias_kind":"pith_short_12","alias_value":"3ZA3T4JJ5SZ2","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_16","alias_value":"3ZA3T4JJ5SZ27FJM","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_8","alias_value":"3ZA3T4JJ","created_at":"2026-05-18T12:29:02.477457+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/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD","json":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD.json","graph_json":"https://pith.science/api/pith-number/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/graph.json","events_json":"https://pith.science/api/pith-number/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/events.json","paper":"https://pith.science/paper/3ZA3T4JJ"},"agent_actions":{"view_html":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD","download_json":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD.json","view_paper":"https://pith.science/paper/3ZA3T4JJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1511.01509&json=true","fetch_graph":"https://pith.science/api/pith-number/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/graph.json","fetch_events":"https://pith.science/api/pith-number/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/action/storage_attestation","attest_author":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/action/author_attestation","sign_citation":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/action/citation_signature","submit_replication":"https://pith.science/pith/3ZA3T4JJ5SZ27FJMZ4D3LWXGFD/action/replication_record"}},"created_at":"2026-05-18T01:27:45.401025+00:00","updated_at":"2026-05-18T01:27:45.401025+00:00"}