{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:XCC32J2WKF4TVWBPVNM42W4WPS","short_pith_number":"pith:XCC32J2W","schema_version":"1.0","canonical_sha256":"b885bd275651793ad82fab59cd5b967ca6d251947385a194af18a8b431b6f367","source":{"kind":"arxiv","id":"1901.05682","version":1},"attestation_state":"computed","paper":{"title":"Exact Spectral-Like Gradient Method for Distributed Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Dusan Jakovetic, Natasa Krejic, Natasa Krklec Jerinkic","submitted_at":"2019-01-17T08:47:34Z","abstract_excerpt":"Since the initial proposal in the late 80s, spectral gradient methods continue to receive significant attention, especially due to their excellent numerical performance on various large scale applications. However, to date, they have not been sufficiently explored in the context of distributed optimization. In this paper, we consider unconstrained distributed optimization problems where $n$ nodes constitute an arbitrary connected network and collaboratively minimize the sum of their local convex cost functions. In this setting, building from existing exact distributed gradient methods, we prop"},"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":"1901.05682","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-01-17T08:47:34Z","cross_cats_sorted":[],"title_canon_sha256":"2c376b1dde0c10394e002fc4b70b00d38b33690808e634b589aa0916fb7d3eac","abstract_canon_sha256":"a846213f72d88cba910128544b3fcf6e31616522b1fe19b41a5b6d26dffce47e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:06.433481Z","signature_b64":"b9cWtJJPXGwk+9zz0Tq88CzZTg+gWxSpbZ1viXxs7G/T4Qz4mQ6RND+IodfVIoj4lvHltsZuRE+1HZXIjgyLDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b885bd275651793ad82fab59cd5b967ca6d251947385a194af18a8b431b6f367","last_reissued_at":"2026-05-17T23:56:06.432778Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:06.432778Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Exact Spectral-Like Gradient Method for Distributed Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Dusan Jakovetic, Natasa Krejic, Natasa Krklec Jerinkic","submitted_at":"2019-01-17T08:47:34Z","abstract_excerpt":"Since the initial proposal in the late 80s, spectral gradient methods continue to receive significant attention, especially due to their excellent numerical performance on various large scale applications. However, to date, they have not been sufficiently explored in the context of distributed optimization. In this paper, we consider unconstrained distributed optimization problems where $n$ nodes constitute an arbitrary connected network and collaboratively minimize the sum of their local convex cost functions. In this setting, building from existing exact distributed gradient methods, we prop"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.05682","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":"1901.05682","created_at":"2026-05-17T23:56:06.432889+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.05682v1","created_at":"2026-05-17T23:56:06.432889+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.05682","created_at":"2026-05-17T23:56:06.432889+00:00"},{"alias_kind":"pith_short_12","alias_value":"XCC32J2WKF4T","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_16","alias_value":"XCC32J2WKF4TVWBP","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_8","alias_value":"XCC32J2W","created_at":"2026-05-18T12:33:33.725879+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/XCC32J2WKF4TVWBPVNM42W4WPS","json":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS.json","graph_json":"https://pith.science/api/pith-number/XCC32J2WKF4TVWBPVNM42W4WPS/graph.json","events_json":"https://pith.science/api/pith-number/XCC32J2WKF4TVWBPVNM42W4WPS/events.json","paper":"https://pith.science/paper/XCC32J2W"},"agent_actions":{"view_html":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS","download_json":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS.json","view_paper":"https://pith.science/paper/XCC32J2W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.05682&json=true","fetch_graph":"https://pith.science/api/pith-number/XCC32J2WKF4TVWBPVNM42W4WPS/graph.json","fetch_events":"https://pith.science/api/pith-number/XCC32J2WKF4TVWBPVNM42W4WPS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS/action/storage_attestation","attest_author":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS/action/author_attestation","sign_citation":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS/action/citation_signature","submit_replication":"https://pith.science/pith/XCC32J2WKF4TVWBPVNM42W4WPS/action/replication_record"}},"created_at":"2026-05-17T23:56:06.432889+00:00","updated_at":"2026-05-17T23:56:06.432889+00:00"}