{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:RDVP2ANWQNXABRCL3BIF32SRXG","short_pith_number":"pith:RDVP2ANW","schema_version":"1.0","canonical_sha256":"88eafd01b6836e00c44bd8505dea51b9b3340bac3d05107166f3421331f291a0","source":{"kind":"arxiv","id":"1501.01242","version":2},"attestation_state":"computed","paper":{"title":"Efficient Online Relative Comparison Kernel Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"(2) Air Force Research Laboratory, Eric Heim (1), Information Directorate), Lee M. Seversky (2), Matthew Berger (2), Milos Hauskrecht (1) ((1) University of Pittsburgh","submitted_at":"2015-01-06T17:19:06Z","abstract_excerpt":"Learning a kernel matrix from relative comparison human feedback is an important problem with applications in collaborative filtering, object retrieval, and search. For learning a kernel over a large number of objects, existing methods face significant scalability issues inhibiting the application of these methods to settings where a kernel is learned in an online and timely fashion. In this paper we propose a novel framework called Efficient online Relative comparison Kernel LEarning (ERKLE), for efficiently learning the similarity of a large set of objects in an online manner. We learn a ker"},"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":"1501.01242","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-01-06T17:19:06Z","cross_cats_sorted":[],"title_canon_sha256":"c9174551bda85ccc1cc0993b6f587299af56b7149a1b964d1ab07dc17ce5a1b9","abstract_canon_sha256":"131cf4ea7d95807b4c6e53475a4e0ee7ab6a9d1f93b69d0aa9ae1aeddb8cefb0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:29:38.407632Z","signature_b64":"gWnATDSbnEKO7YCX4Gbh7Ng3oO7AEdpSK5hN62t+j9+PdDVf+hiRx/9SaIo1sqjy3lSVHWzCunPOiFmojRZKDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"88eafd01b6836e00c44bd8505dea51b9b3340bac3d05107166f3421331f291a0","last_reissued_at":"2026-05-18T02:29:38.407260Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:29:38.407260Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient Online Relative Comparison Kernel Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"(2) Air Force Research Laboratory, Eric Heim (1), Information Directorate), Lee M. Seversky (2), Matthew Berger (2), Milos Hauskrecht (1) ((1) University of Pittsburgh","submitted_at":"2015-01-06T17:19:06Z","abstract_excerpt":"Learning a kernel matrix from relative comparison human feedback is an important problem with applications in collaborative filtering, object retrieval, and search. For learning a kernel over a large number of objects, existing methods face significant scalability issues inhibiting the application of these methods to settings where a kernel is learned in an online and timely fashion. In this paper we propose a novel framework called Efficient online Relative comparison Kernel LEarning (ERKLE), for efficiently learning the similarity of a large set of objects in an online manner. We learn a ker"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1501.01242","kind":"arxiv","version":2},"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":"1501.01242","created_at":"2026-05-18T02:29:38.407322+00:00"},{"alias_kind":"arxiv_version","alias_value":"1501.01242v2","created_at":"2026-05-18T02:29:38.407322+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1501.01242","created_at":"2026-05-18T02:29:38.407322+00:00"},{"alias_kind":"pith_short_12","alias_value":"RDVP2ANWQNXA","created_at":"2026-05-18T12:29:39.896362+00:00"},{"alias_kind":"pith_short_16","alias_value":"RDVP2ANWQNXABRCL","created_at":"2026-05-18T12:29:39.896362+00:00"},{"alias_kind":"pith_short_8","alias_value":"RDVP2ANW","created_at":"2026-05-18T12:29:39.896362+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/RDVP2ANWQNXABRCL3BIF32SRXG","json":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG.json","graph_json":"https://pith.science/api/pith-number/RDVP2ANWQNXABRCL3BIF32SRXG/graph.json","events_json":"https://pith.science/api/pith-number/RDVP2ANWQNXABRCL3BIF32SRXG/events.json","paper":"https://pith.science/paper/RDVP2ANW"},"agent_actions":{"view_html":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG","download_json":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG.json","view_paper":"https://pith.science/paper/RDVP2ANW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1501.01242&json=true","fetch_graph":"https://pith.science/api/pith-number/RDVP2ANWQNXABRCL3BIF32SRXG/graph.json","fetch_events":"https://pith.science/api/pith-number/RDVP2ANWQNXABRCL3BIF32SRXG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG/action/storage_attestation","attest_author":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG/action/author_attestation","sign_citation":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG/action/citation_signature","submit_replication":"https://pith.science/pith/RDVP2ANWQNXABRCL3BIF32SRXG/action/replication_record"}},"created_at":"2026-05-18T02:29:38.407322+00:00","updated_at":"2026-05-18T02:29:38.407322+00:00"}