{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:BHUYBVU3SCQSAATWWB3F2GD3WA","short_pith_number":"pith:BHUYBVU3","schema_version":"1.0","canonical_sha256":"09e980d69b90a1200276b0765d187bb03f14a9fad06829f6955647dfee620e5c","source":{"kind":"arxiv","id":"1704.01415","version":1},"attestation_state":"computed","paper":{"title":"Multi-Label Learning with Global and Local Label Correlation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"James T. Kwok, Yue Zhu, Zhi-Hua Zhou","submitted_at":"2017-04-04T12:50:25Z","abstract_excerpt":"It is well-known that exploiting label correlations is important to multi-label learning. Existing approaches either assume that the label correlations are global and shared by all instances; or that the label correlations are local and shared only by a data subset. In fact, in the real-world applications, both cases may occur that some label correlations are globally applicable and some are shared only in a local group of instances. Moreover, it is also a usual case that only partial labels are observed, which makes the exploitation of the label correlations much more difficult. That is, it i"},"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":"1704.01415","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-04-04T12:50:25Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c18e3de5e611f37359dc8abaed07d9e68241349866addf9d38dc82d8598b470f","abstract_canon_sha256":"32662fb272377a7c3f3e7fae8cd02f084f145dca7d13f21ecdb4a064726e9353"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:46:58.220605Z","signature_b64":"zSezl9ruKE0Daoschkthlg3vqUDI60zTCDnxYMhLZ7gFUEO7TyfwqXza3i15CAfvzqpuuhOqZyo4Y/BvaNctDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"09e980d69b90a1200276b0765d187bb03f14a9fad06829f6955647dfee620e5c","last_reissued_at":"2026-05-18T00:46:58.220139Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:46:58.220139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multi-Label Learning with Global and Local Label Correlation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"James T. Kwok, Yue Zhu, Zhi-Hua Zhou","submitted_at":"2017-04-04T12:50:25Z","abstract_excerpt":"It is well-known that exploiting label correlations is important to multi-label learning. Existing approaches either assume that the label correlations are global and shared by all instances; or that the label correlations are local and shared only by a data subset. In fact, in the real-world applications, both cases may occur that some label correlations are globally applicable and some are shared only in a local group of instances. Moreover, it is also a usual case that only partial labels are observed, which makes the exploitation of the label correlations much more difficult. That is, it i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01415","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":"1704.01415","created_at":"2026-05-18T00:46:58.220203+00:00"},{"alias_kind":"arxiv_version","alias_value":"1704.01415v1","created_at":"2026-05-18T00:46:58.220203+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01415","created_at":"2026-05-18T00:46:58.220203+00:00"},{"alias_kind":"pith_short_12","alias_value":"BHUYBVU3SCQS","created_at":"2026-05-18T12:31:08.081275+00:00"},{"alias_kind":"pith_short_16","alias_value":"BHUYBVU3SCQSAATW","created_at":"2026-05-18T12:31:08.081275+00:00"},{"alias_kind":"pith_short_8","alias_value":"BHUYBVU3","created_at":"2026-05-18T12:31:08.081275+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/BHUYBVU3SCQSAATWWB3F2GD3WA","json":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA.json","graph_json":"https://pith.science/api/pith-number/BHUYBVU3SCQSAATWWB3F2GD3WA/graph.json","events_json":"https://pith.science/api/pith-number/BHUYBVU3SCQSAATWWB3F2GD3WA/events.json","paper":"https://pith.science/paper/BHUYBVU3"},"agent_actions":{"view_html":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA","download_json":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA.json","view_paper":"https://pith.science/paper/BHUYBVU3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1704.01415&json=true","fetch_graph":"https://pith.science/api/pith-number/BHUYBVU3SCQSAATWWB3F2GD3WA/graph.json","fetch_events":"https://pith.science/api/pith-number/BHUYBVU3SCQSAATWWB3F2GD3WA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA/action/storage_attestation","attest_author":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA/action/author_attestation","sign_citation":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA/action/citation_signature","submit_replication":"https://pith.science/pith/BHUYBVU3SCQSAATWWB3F2GD3WA/action/replication_record"}},"created_at":"2026-05-18T00:46:58.220203+00:00","updated_at":"2026-05-18T00:46:58.220203+00:00"}