{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:KVIBKDEWJ3KF6V7337FGL3V3XI","short_pith_number":"pith:KVIBKDEW","schema_version":"1.0","canonical_sha256":"5550150c964ed45f57fbdfca65eebbba1b07803320b5994e2f88eaeaa0541b4f","source":{"kind":"arxiv","id":"1212.2494","version":1},"attestation_state":"computed","paper":{"title":"Learning Generative Models of Similarity Matrices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Brendan J. Frey, Romer Rosales","submitted_at":"2012-10-19T15:07:42Z","abstract_excerpt":"We describe a probabilistic (generative) view of affinity matrices along with     inference algorithms for a subclass of problems associated with data     clustering. This probabilistic view is helpful in understanding different     models and algorithms that are based on affinity functions      OF the data. IN particular, we show how(greedy) inference FOR     a specific probabilistic model IS equivalent TO the spectral clustering      algorithm.It also provides a framework FOR developing new algorithms AND     extended models. AS one CASE, we present new generative data clustering models that"},"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":"1212.2494","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2012-10-19T15:07:42Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"4fdd9b5bcfbce756ecf55e4e923ed3d5f7d46125acd39bd8dcd5de0a380c9bb0","abstract_canon_sha256":"44947f842384eec4f37458f98b8d871f2b9a02cc842c0a3ae892687e7653cde7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:38:44.581191Z","signature_b64":"9+2JOaaChhKbvTfb50pzAXzdFeHrtp1r4WVGE+5VrfXaxmksuGeK3F69ioNAvQGjplHNUGr9b9xn+XuCQ8/HCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5550150c964ed45f57fbdfca65eebbba1b07803320b5994e2f88eaeaa0541b4f","last_reissued_at":"2026-05-18T03:38:44.580499Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:38:44.580499Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning Generative Models of Similarity Matrices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Brendan J. Frey, Romer Rosales","submitted_at":"2012-10-19T15:07:42Z","abstract_excerpt":"We describe a probabilistic (generative) view of affinity matrices along with     inference algorithms for a subclass of problems associated with data     clustering. This probabilistic view is helpful in understanding different     models and algorithms that are based on affinity functions      OF the data. IN particular, we show how(greedy) inference FOR     a specific probabilistic model IS equivalent TO the spectral clustering      algorithm.It also provides a framework FOR developing new algorithms AND     extended models. AS one CASE, we present new generative data clustering models that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1212.2494","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":"1212.2494","created_at":"2026-05-18T03:38:44.580609+00:00"},{"alias_kind":"arxiv_version","alias_value":"1212.2494v1","created_at":"2026-05-18T03:38:44.580609+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1212.2494","created_at":"2026-05-18T03:38:44.580609+00:00"},{"alias_kind":"pith_short_12","alias_value":"KVIBKDEWJ3KF","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_16","alias_value":"KVIBKDEWJ3KF6V73","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_8","alias_value":"KVIBKDEW","created_at":"2026-05-18T12:27:11.947152+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/KVIBKDEWJ3KF6V7337FGL3V3XI","json":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI.json","graph_json":"https://pith.science/api/pith-number/KVIBKDEWJ3KF6V7337FGL3V3XI/graph.json","events_json":"https://pith.science/api/pith-number/KVIBKDEWJ3KF6V7337FGL3V3XI/events.json","paper":"https://pith.science/paper/KVIBKDEW"},"agent_actions":{"view_html":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI","download_json":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI.json","view_paper":"https://pith.science/paper/KVIBKDEW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1212.2494&json=true","fetch_graph":"https://pith.science/api/pith-number/KVIBKDEWJ3KF6V7337FGL3V3XI/graph.json","fetch_events":"https://pith.science/api/pith-number/KVIBKDEWJ3KF6V7337FGL3V3XI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI/action/storage_attestation","attest_author":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI/action/author_attestation","sign_citation":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI/action/citation_signature","submit_replication":"https://pith.science/pith/KVIBKDEWJ3KF6V7337FGL3V3XI/action/replication_record"}},"created_at":"2026-05-18T03:38:44.580609+00:00","updated_at":"2026-05-18T03:38:44.580609+00:00"}