{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4DRSGSSAFTOP4A5WNLD5EZ6JTR","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":"ccd1f1798b153813b9fdfeddc1a11d30908a3341b48e5da4f62979950f9ae3c9","cross_cats_sorted":["cs.DS","math.ST","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-24T16:54:46Z","title_canon_sha256":"753d4a5d0854ddd20793c3b9c14fcd0d1e9e5649bae87801b4477f8cd89a8f66"},"schema_version":"1.0","source":{"id":"1906.10075","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.10075","created_at":"2026-07-05T00:25:11Z"},{"alias_kind":"arxiv_version","alias_value":"1906.10075v2","created_at":"2026-07-05T00:25:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.10075","created_at":"2026-07-05T00:25:11Z"},{"alias_kind":"pith_short_12","alias_value":"4DRSGSSAFTOP","created_at":"2026-07-05T00:25:11Z"},{"alias_kind":"pith_short_16","alias_value":"4DRSGSSAFTOP4A5W","created_at":"2026-07-05T00:25:11Z"},{"alias_kind":"pith_short_8","alias_value":"4DRSGSSA","created_at":"2026-07-05T00:25:11Z"}],"graph_snapshots":[{"event_id":"sha256:603c2dd799b0fd32a41176a9fd10891f1e06d571b5c942381e116441c1f53b08","target":"graph","created_at":"2026-07-05T00:25:11Z","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/1906.10075/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study the problem of {\\em distribution-independent} PAC learning of halfspaces in the presence of Massart noise. Specifically, we are given a set of labeled examples $(\\mathbf{x}, y)$ drawn from a distribution $\\mathcal{D}$ on $\\mathbb{R}^{d+1}$ such that the marginal distribution on the unlabeled points $\\mathbf{x}$ is arbitrary and the labels $y$ are generated by an unknown halfspace corrupted with Massart noise at noise rate $\\eta<1/2$. The goal is to find a hypothesis $h$ that minimizes the misclassification error $\\mathbf{Pr}_{(\\mathbf{x}, y) \\sim \\mathcal{D}} \\left[ h(\\mathbf{x}) \\neq","authors_text":"Christos Tzamos, Ilias Diakonikolas, Themis Gouleakis","cross_cats":["cs.DS","math.ST","stat.ML","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-24T16:54:46Z","title":"Distribution-Independent PAC Learning of Halfspaces with Massart Noise"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.10075","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:bbbedc3c884c16f234efdf492b7d9cd455c809871fdc1a09185341bcda908ad0","target":"record","created_at":"2026-07-05T00:25:11Z","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":"ccd1f1798b153813b9fdfeddc1a11d30908a3341b48e5da4f62979950f9ae3c9","cross_cats_sorted":["cs.DS","math.ST","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-24T16:54:46Z","title_canon_sha256":"753d4a5d0854ddd20793c3b9c14fcd0d1e9e5649bae87801b4477f8cd89a8f66"},"schema_version":"1.0","source":{"id":"1906.10075","kind":"arxiv","version":2}},"canonical_sha256":"e0e3234a402cdcfe03b66ac7d267c99c7c60a8efd345846d6c99605fb6a9e5cb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0e3234a402cdcfe03b66ac7d267c99c7c60a8efd345846d6c99605fb6a9e5cb","first_computed_at":"2026-07-05T00:25:11.483276Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:25:11.483276Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L+cOzJp/5txWYj3V0AQh8R/UnV3Fznn3TUTkSCdg7R806y8SQ8ExCs/5bTkQqsyNsVTI1PBkSUAcewEST7tUCA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:25:11.483702Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.10075","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bbbedc3c884c16f234efdf492b7d9cd455c809871fdc1a09185341bcda908ad0","sha256:603c2dd799b0fd32a41176a9fd10891f1e06d571b5c942381e116441c1f53b08"],"state_sha256":"e36aa9825e8ddaff25d763f20a54ca3ea3cfa70b2ffaeb270127f51389a1b7f9"}