{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:VMRQUBQMDPZFYSEFRLMHBUM2ED","short_pith_number":"pith:VMRQUBQM","schema_version":"1.0","canonical_sha256":"ab230a060c1bf25c48858ad870d19a20f99df8bbcde5b15e39086c0fcf1b89fc","source":{"kind":"arxiv","id":"1710.00032","version":1},"attestation_state":"computed","paper":{"title":"Learning the Exact Topology of Undirected Consensus Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SY","authors_text":"Deepjyoti Deka, Donatello Materassi, Murti V. Salapaka, Sandeep Attree, Saurav Talukdar","submitted_at":"2017-09-29T18:57:39Z","abstract_excerpt":"In this article, we present a method to learn the interaction topology of a network of agents undergoing linear consensus updates in a non invasive manner. Our approach is based on multivariate Wiener filtering, which is known to recover spurious edges apart from the true edges in the topology. The main contribution of this work is to show that in the case of undirected consensus networks, all spurious links obtained using Wiener filtering can be identified using frequency response of the Wiener filters. Thus, the exact interaction topology of the agents is unveiled. The method presented requi"},"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":"1710.00032","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2017-09-29T18:57:39Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"725010f0ebf72e89003ef087afa63d729079db231e2a460505626a262de4358b","abstract_canon_sha256":"4fafd163ba22f291afcd9ed5b7c7cf96173fde1c6924c79e09d01b9932cac1a9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:58.070669Z","signature_b64":"WhYD4Jm2QO1IiF7rXLp9hu/IDLW+6Reab93LyxthF0R9wd/3Tchgz5AKGE4Ak7rgIgg29nTeuoOYxAp6WEFEBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ab230a060c1bf25c48858ad870d19a20f99df8bbcde5b15e39086c0fcf1b89fc","last_reissued_at":"2026-05-18T00:33:58.069963Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:58.069963Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning the Exact Topology of Undirected Consensus Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SY","authors_text":"Deepjyoti Deka, Donatello Materassi, Murti V. Salapaka, Sandeep Attree, Saurav Talukdar","submitted_at":"2017-09-29T18:57:39Z","abstract_excerpt":"In this article, we present a method to learn the interaction topology of a network of agents undergoing linear consensus updates in a non invasive manner. Our approach is based on multivariate Wiener filtering, which is known to recover spurious edges apart from the true edges in the topology. The main contribution of this work is to show that in the case of undirected consensus networks, all spurious links obtained using Wiener filtering can be identified using frequency response of the Wiener filters. Thus, the exact interaction topology of the agents is unveiled. The method presented requi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.00032","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":"1710.00032","created_at":"2026-05-18T00:33:58.070065+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.00032v1","created_at":"2026-05-18T00:33:58.070065+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.00032","created_at":"2026-05-18T00:33:58.070065+00:00"},{"alias_kind":"pith_short_12","alias_value":"VMRQUBQMDPZF","created_at":"2026-05-18T12:31:49.984773+00:00"},{"alias_kind":"pith_short_16","alias_value":"VMRQUBQMDPZFYSEF","created_at":"2026-05-18T12:31:49.984773+00:00"},{"alias_kind":"pith_short_8","alias_value":"VMRQUBQM","created_at":"2026-05-18T12:31:49.984773+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/VMRQUBQMDPZFYSEFRLMHBUM2ED","json":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED.json","graph_json":"https://pith.science/api/pith-number/VMRQUBQMDPZFYSEFRLMHBUM2ED/graph.json","events_json":"https://pith.science/api/pith-number/VMRQUBQMDPZFYSEFRLMHBUM2ED/events.json","paper":"https://pith.science/paper/VMRQUBQM"},"agent_actions":{"view_html":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED","download_json":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED.json","view_paper":"https://pith.science/paper/VMRQUBQM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.00032&json=true","fetch_graph":"https://pith.science/api/pith-number/VMRQUBQMDPZFYSEFRLMHBUM2ED/graph.json","fetch_events":"https://pith.science/api/pith-number/VMRQUBQMDPZFYSEFRLMHBUM2ED/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED/action/storage_attestation","attest_author":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED/action/author_attestation","sign_citation":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED/action/citation_signature","submit_replication":"https://pith.science/pith/VMRQUBQMDPZFYSEFRLMHBUM2ED/action/replication_record"}},"created_at":"2026-05-18T00:33:58.070065+00:00","updated_at":"2026-05-18T00:33:58.070065+00:00"}