{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:AEK4ZFBMFSUT6XLCYTP53KCQHX","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":"36db0fa00e7880ed0ee417ede0622061b9b324b6f180beffb304efb9d531fa47","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-06T04:02:35Z","title_canon_sha256":"dbf781f55b284becbb0ade5595267e34a7c9e0d6712452346983c39e494229f2"},"schema_version":"1.0","source":{"id":"1704.01701","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.01701","created_at":"2026-05-18T00:08:55Z"},{"alias_kind":"arxiv_version","alias_value":"1704.01701v4","created_at":"2026-05-18T00:08:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01701","created_at":"2026-05-18T00:08:55Z"},{"alias_kind":"pith_short_12","alias_value":"AEK4ZFBMFSUT","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_16","alias_value":"AEK4ZFBMFSUT6XLC","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_8","alias_value":"AEK4ZFBM","created_at":"2026-05-18T12:31:05Z"}],"graph_snapshots":[{"event_id":"sha256:b835ff21352ac7ae7bb4ed1595898b747ab1bf270e539f008666b34eebaaa7d2","target":"graph","created_at":"2026-05-18T00:08:55Z","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"},"paper":{"abstract_excerpt":"We present the design and implementation of a custom discrete optimization technique for building rule lists over a categorical feature space. Our algorithm produces rule lists with optimal training performance, according to the regularized empirical risk, with a certificate of optimality. By leveraging algorithmic bounds, efficient data structures, and computational reuse, we achieve several orders of magnitude speedup in time and a massive reduction of memory consumption. We demonstrate that our approach produces optimal rule lists on practical problems in seconds. Our results indicate that ","authors_text":"Cynthia Rudin, Daniel Alabi, Elaine Angelino, Margo Seltzer, Nicholas Larus-Stone","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-06T04:02:35Z","title":"Learning Certifiably Optimal Rule Lists for Categorical Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01701","kind":"arxiv","version":4},"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":"sha256:961e18707858463841b058f9e78de0c1bc795d46bc3c967955d4389ab29b0b43","target":"record","created_at":"2026-05-18T00:08:55Z","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":"36db0fa00e7880ed0ee417ede0622061b9b324b6f180beffb304efb9d531fa47","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-06T04:02:35Z","title_canon_sha256":"dbf781f55b284becbb0ade5595267e34a7c9e0d6712452346983c39e494229f2"},"schema_version":"1.0","source":{"id":"1704.01701","kind":"arxiv","version":4}},"canonical_sha256":"0115cc942c2ca93f5d62c4dfdda8503dfb3465377ad7c083aef9d0b687592357","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0115cc942c2ca93f5d62c4dfdda8503dfb3465377ad7c083aef9d0b687592357","first_computed_at":"2026-05-18T00:08:55.415661Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:08:55.415661Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"J6BelDIdGWTGMOn3YXLYhpm0G/E+aOSLUXsu7ApZSkddg4pcxeKfpK0nLkxQXJ9dKOP5PGB4V2VahX9bHrr4Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:08:55.416174Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.01701","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:961e18707858463841b058f9e78de0c1bc795d46bc3c967955d4389ab29b0b43","sha256:b835ff21352ac7ae7bb4ed1595898b747ab1bf270e539f008666b34eebaaa7d2"],"state_sha256":"9dfd51356cf1fcf11f3acdc5b63b57c41f3d184e1436bd7b7b966070cd0fe093"}