{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:FWZ3RFXWPZ2YLSSRK6KVZ5O4HR","short_pith_number":"pith:FWZ3RFXW","schema_version":"1.0","canonical_sha256":"2db3b896f67e7585ca5157955cf5dc3c50199e9edd1e1ef8b4b25cb081db67ef","source":{"kind":"arxiv","id":"1806.00640","version":1},"attestation_state":"computed","paper":{"title":"Binary Classification with Karmic, Threshold-Quasi-Concave Metrics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Bowei Yan, Kai Zhong, Oluwasanmi Koyejo, Pradeep Ravikumar","submitted_at":"2018-06-02T14:12:24Z","abstract_excerpt":"Complex performance measures, beyond the popular measure of accuracy, are increasingly being used in the context of binary classification. These complex performance measures are typically not even decomposable, that is, the loss evaluated on a batch of samples cannot typically be expressed as a sum or average of losses evaluated at individual samples, which in turn requires new theoretical and methodological developments beyond standard treatments of supervised learning. In this paper, we advance this understanding of binary classification for complex performance measures by identifying two ke"},"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":"1806.00640","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-02T14:12:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8dc4d6de69a0ed922158f7e72dd0c93f2700ef17f379fe754719019f5735158d","abstract_canon_sha256":"8cc2e93f042858656222524aadf4d1bda8703010d88c4d4bd3155e7470c8f0aa"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:18.837848Z","signature_b64":"0KzG4GjcrL40aFtJ0ZrGlalKWvMcsnLMBV73uHOCsPEcLQdlMHC/FT0KaMcUjK+z8x61F5RrWAvLv9cIN27TBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2db3b896f67e7585ca5157955cf5dc3c50199e9edd1e1ef8b4b25cb081db67ef","last_reissued_at":"2026-05-18T00:14:18.837369Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:18.837369Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Binary Classification with Karmic, Threshold-Quasi-Concave Metrics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Bowei Yan, Kai Zhong, Oluwasanmi Koyejo, Pradeep Ravikumar","submitted_at":"2018-06-02T14:12:24Z","abstract_excerpt":"Complex performance measures, beyond the popular measure of accuracy, are increasingly being used in the context of binary classification. These complex performance measures are typically not even decomposable, that is, the loss evaluated on a batch of samples cannot typically be expressed as a sum or average of losses evaluated at individual samples, which in turn requires new theoretical and methodological developments beyond standard treatments of supervised learning. In this paper, we advance this understanding of binary classification for complex performance measures by identifying two ke"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00640","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":"1806.00640","created_at":"2026-05-18T00:14:18.837452+00:00"},{"alias_kind":"arxiv_version","alias_value":"1806.00640v1","created_at":"2026-05-18T00:14:18.837452+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00640","created_at":"2026-05-18T00:14:18.837452+00:00"},{"alias_kind":"pith_short_12","alias_value":"FWZ3RFXWPZ2Y","created_at":"2026-05-18T12:32:25.280505+00:00"},{"alias_kind":"pith_short_16","alias_value":"FWZ3RFXWPZ2YLSSR","created_at":"2026-05-18T12:32:25.280505+00:00"},{"alias_kind":"pith_short_8","alias_value":"FWZ3RFXW","created_at":"2026-05-18T12:32:25.280505+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/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR","json":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR.json","graph_json":"https://pith.science/api/pith-number/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/graph.json","events_json":"https://pith.science/api/pith-number/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/events.json","paper":"https://pith.science/paper/FWZ3RFXW"},"agent_actions":{"view_html":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR","download_json":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR.json","view_paper":"https://pith.science/paper/FWZ3RFXW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1806.00640&json=true","fetch_graph":"https://pith.science/api/pith-number/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/graph.json","fetch_events":"https://pith.science/api/pith-number/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/action/storage_attestation","attest_author":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/action/author_attestation","sign_citation":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/action/citation_signature","submit_replication":"https://pith.science/pith/FWZ3RFXWPZ2YLSSRK6KVZ5O4HR/action/replication_record"}},"created_at":"2026-05-18T00:14:18.837452+00:00","updated_at":"2026-05-18T00:14:18.837452+00:00"}