{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:DHVMG5QLDHKI7PRJMR5QMN7XVX","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"91431f217de5a1401de5c9e4072410ae5051566da942b6363d25058dd82e17ea","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-09-09T16:37:14Z","title_canon_sha256":"3453ce89f1789d279c0306eb26a3ab9c6eb200d52b28b8c487a022ad8c94e364"},"schema_version":"1.0","source":{"id":"1909.03977","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1909.03977","created_at":"2026-07-05T00:41:12Z"},{"alias_kind":"arxiv_version","alias_value":"1909.03977v2","created_at":"2026-07-05T00:41:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.03977","created_at":"2026-07-05T00:41:12Z"},{"alias_kind":"pith_short_12","alias_value":"DHVMG5QLDHKI","created_at":"2026-07-05T00:41:12Z"},{"alias_kind":"pith_short_16","alias_value":"DHVMG5QLDHKI7PRJ","created_at":"2026-07-05T00:41:12Z"},{"alias_kind":"pith_short_8","alias_value":"DHVMG5QL","created_at":"2026-07-05T00:41:12Z"}],"graph_snapshots":[{"event_id":"sha256:2aaa6d6d6138ba0361bf2baa0039f7694109521b818ec69e129f5bd2c63a4547","target":"graph","created_at":"2026-07-05T00:41:12Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1909.03977/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As the use of black-box models becomes ubiquitous in high stake decision-making systems, demands for fair and interpretable models are increasing. While it has been shown that interpretable models can be as accurate as black-box models in several critical domains, existing fair classification techniques that are interpretable by design often display poor accuracy/fairness tradeoffs in comparison with their non-interpretable counterparts. In this paper, we propose FairCORELS, a fair classification technique interpretable by design, whose objective is to learn fair rule lists. Our solution is a ","authors_text":"Julien Ferry, Marie-Jos\\'e Huguet, Mohamed Siala, S\\'ebastien Gambs, Ulrich A\\\"ivodji","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-09-09T16:37:14Z","title":"Learning Fair Rule Lists"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.03977","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7bcb16a8868c4445ac462dc1873ebc3c77bd6644d36a95997b5c2dff07a882f3","target":"record","created_at":"2026-07-05T00:41:12Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"91431f217de5a1401de5c9e4072410ae5051566da942b6363d25058dd82e17ea","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-09-09T16:37:14Z","title_canon_sha256":"3453ce89f1789d279c0306eb26a3ab9c6eb200d52b28b8c487a022ad8c94e364"},"schema_version":"1.0","source":{"id":"1909.03977","kind":"arxiv","version":2}},"canonical_sha256":"19eac3760b19d48fbe29647b0637f7adc00300c58288b3091207b3f0b6b64ece","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"19eac3760b19d48fbe29647b0637f7adc00300c58288b3091207b3f0b6b64ece","first_computed_at":"2026-07-05T00:41:12.887760Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:41:12.887760Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FkDPt9KMiN/KLnDDW9ew03IR69DXaWBf5gcb6Db/1qzow6R0L4FjR+Uzldr9/ThNjxEAS+/YwdfkJTb7c1tUBw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:41:12.888105Z","signed_message":"canonical_sha256_bytes"},"source_id":"1909.03977","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7bcb16a8868c4445ac462dc1873ebc3c77bd6644d36a95997b5c2dff07a882f3","sha256:2aaa6d6d6138ba0361bf2baa0039f7694109521b818ec69e129f5bd2c63a4547"],"state_sha256":"ecd950a57594dec0ffce22c279685093394599b3387fc19e57b74e80a455b323"}