{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:SAI6FKJUPH3VYG3WHHXZMFCL7U","short_pith_number":"pith:SAI6FKJU","schema_version":"1.0","canonical_sha256":"9011e2a93479f75c1b7639ef96144bfd2c2e0128ab9e91ba0109354ce5e56931","source":{"kind":"arxiv","id":"1203.2808","version":1},"attestation_state":"computed","paper":{"title":"A Distributed Line Search for Network Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Alejandro Ribeiro, Ali Jadbabaie, Michael Zargham","submitted_at":"2012-03-13T13:47:37Z","abstract_excerpt":"Dual descent methods are used to solve network optimization problems because descent directions can be computed in a distributed manner using information available either locally or at neighboring nodes. However, choosing a stepsize in the descent direction remains a challenge because its computation requires global information. This work presents an algorithm based on a local version of the Armijo rule that allows for the computation of a stepsize using only local and neighborhood information. We show that when our distributed line search algorithm is applied with a descent direction computed"},"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":"1203.2808","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2012-03-13T13:47:37Z","cross_cats_sorted":[],"title_canon_sha256":"dc88f8a2002f6d991f7b6cf5d5022f2f39aeb19e1e588a74397c8d01ae37f1b5","abstract_canon_sha256":"fc5bd33cc6eb39674376d0153bae591d4853282ff9d4125470f652ef77f246b4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:00:14.545560Z","signature_b64":"WjPsVxf4nh3MaSHF6JS5ukZG1iJ3l3rie55MigrJbzZYYfUCvPs5ZPZg2yEOGRuQe97Ou4NjkKZYU8g9nd2ABw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9011e2a93479f75c1b7639ef96144bfd2c2e0128ab9e91ba0109354ce5e56931","last_reissued_at":"2026-05-18T04:00:14.544743Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:00:14.544743Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Distributed Line Search for Network Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Alejandro Ribeiro, Ali Jadbabaie, Michael Zargham","submitted_at":"2012-03-13T13:47:37Z","abstract_excerpt":"Dual descent methods are used to solve network optimization problems because descent directions can be computed in a distributed manner using information available either locally or at neighboring nodes. However, choosing a stepsize in the descent direction remains a challenge because its computation requires global information. This work presents an algorithm based on a local version of the Armijo rule that allows for the computation of a stepsize using only local and neighborhood information. We show that when our distributed line search algorithm is applied with a descent direction computed"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1203.2808","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":"1203.2808","created_at":"2026-05-18T04:00:14.544882+00:00"},{"alias_kind":"arxiv_version","alias_value":"1203.2808v1","created_at":"2026-05-18T04:00:14.544882+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1203.2808","created_at":"2026-05-18T04:00:14.544882+00:00"},{"alias_kind":"pith_short_12","alias_value":"SAI6FKJUPH3V","created_at":"2026-05-18T12:27:20.899486+00:00"},{"alias_kind":"pith_short_16","alias_value":"SAI6FKJUPH3VYG3W","created_at":"2026-05-18T12:27:20.899486+00:00"},{"alias_kind":"pith_short_8","alias_value":"SAI6FKJU","created_at":"2026-05-18T12:27:20.899486+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/SAI6FKJUPH3VYG3WHHXZMFCL7U","json":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U.json","graph_json":"https://pith.science/api/pith-number/SAI6FKJUPH3VYG3WHHXZMFCL7U/graph.json","events_json":"https://pith.science/api/pith-number/SAI6FKJUPH3VYG3WHHXZMFCL7U/events.json","paper":"https://pith.science/paper/SAI6FKJU"},"agent_actions":{"view_html":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U","download_json":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U.json","view_paper":"https://pith.science/paper/SAI6FKJU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1203.2808&json=true","fetch_graph":"https://pith.science/api/pith-number/SAI6FKJUPH3VYG3WHHXZMFCL7U/graph.json","fetch_events":"https://pith.science/api/pith-number/SAI6FKJUPH3VYG3WHHXZMFCL7U/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U/action/storage_attestation","attest_author":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U/action/author_attestation","sign_citation":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U/action/citation_signature","submit_replication":"https://pith.science/pith/SAI6FKJUPH3VYG3WHHXZMFCL7U/action/replication_record"}},"created_at":"2026-05-18T04:00:14.544882+00:00","updated_at":"2026-05-18T04:00:14.544882+00:00"}