{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PEXQE5M4ZC3O3G5JWN3CHTF2XM","short_pith_number":"pith:PEXQE5M4","canonical_record":{"source":{"id":"2408.17165","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:08:21Z","cross_cats_sorted":["cs.DS","stat.ML"],"title_canon_sha256":"b22f3ca7b1bd7f1a187e7eeed056a08582c65a1b1caf6e84ae0fe5efe147c9d2","abstract_canon_sha256":"449240f4c64807c3c14f60511ff0b1925a1006743610c8c96b9b506abea08588"},"schema_version":"1.0"},"canonical_sha256":"792f02759cc8b6ed9ba9b37623ccbabb28b81398d8ffcc46bc46363ae172a70a","source":{"kind":"arxiv","id":"2408.17165","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.17165","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"arxiv_version","alias_value":"2408.17165v1","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.17165","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_12","alias_value":"PEXQE5M4ZC3O","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_16","alias_value":"PEXQE5M4ZC3O3G5J","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_8","alias_value":"PEXQE5M4","created_at":"2026-07-05T09:01:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PEXQE5M4ZC3O3G5JWN3CHTF2XM","target":"record","payload":{"canonical_record":{"source":{"id":"2408.17165","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:08:21Z","cross_cats_sorted":["cs.DS","stat.ML"],"title_canon_sha256":"b22f3ca7b1bd7f1a187e7eeed056a08582c65a1b1caf6e84ae0fe5efe147c9d2","abstract_canon_sha256":"449240f4c64807c3c14f60511ff0b1925a1006743610c8c96b9b506abea08588"},"schema_version":"1.0"},"canonical_sha256":"792f02759cc8b6ed9ba9b37623ccbabb28b81398d8ffcc46bc46363ae172a70a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:01:11.683397Z","signature_b64":"G4EryxwEMUsXnbZgoK66vAohpJDKFcdqUQykySoMDeX3wqEUh/sdniPPWRtyCKJ+eqY/EarA7rksaYV3zEJDAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"792f02759cc8b6ed9ba9b37623ccbabb28b81398d8ffcc46bc46363ae172a70a","last_reissued_at":"2026-07-05T09:01:11.682920Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:01:11.682920Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.17165","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:01:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yFQkm+bktkWvJVkwCf/ZCVfSZB7GTMFZn/JwZc5Nb38afXUxUGCxlqZhYXdkE/hdyzYJfrlc0F0eeJrM1t53AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T05:10:36.641518Z"},"content_sha256":"53f233ba34e6bfe4d4bc2c92c5f431195e8cb23a06e717ead580787878d52d79","schema_version":"1.0","event_id":"sha256:53f233ba34e6bfe4d4bc2c92c5f431195e8cb23a06e717ead580787878d52d79"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PEXQE5M4ZC3O3G5JWN3CHTF2XM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Testable Learning of General Halfspaces with Adversarial Label Noise","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DS","stat.ML"],"primary_cat":"cs.LG","authors_text":"Daniel M. Kane, Ilias Diakonikolas, Nikos Zarifis, Sihan Liu","submitted_at":"2024-08-30T10:08:21Z","abstract_excerpt":"We study the task of testable learning of general -- not necessarily homogeneous -- halfspaces with adversarial label noise with respect to the Gaussian distribution. In the testable learning framework, the goal is to develop a tester-learner such that if the data passes the tester, then one can trust the output of the robust learner on the data.Our main result is the first polynomial time tester-learner for general halfspaces that achieves dimension-independent misclassification error. At the heart of our approach is a new methodology to reduce testable learning of general halfspaces to testa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.17165","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2408.17165/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:01:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I6l1BMJqsnAaF1R17Cm8GpCAIjKTHxLUjJR21ErvlNowW4q3bq/IaIacqLDmXjalqPDUOT04iwrS/v9QuA0iDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T05:10:36.642035Z"},"content_sha256":"9b201944fec05caf30d420c89194fd4e3a2ddec62bd918d5bf7f8b9c12be2462","schema_version":"1.0","event_id":"sha256:9b201944fec05caf30d420c89194fd4e3a2ddec62bd918d5bf7f8b9c12be2462"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PEXQE5M4ZC3O3G5JWN3CHTF2XM/bundle.json","state_url":"https://pith.science/pith/PEXQE5M4ZC3O3G5JWN3CHTF2XM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PEXQE5M4ZC3O3G5JWN3CHTF2XM/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-01T05:10:36Z","links":{"resolver":"https://pith.science/pith/PEXQE5M4ZC3O3G5JWN3CHTF2XM","bundle":"https://pith.science/pith/PEXQE5M4ZC3O3G5JWN3CHTF2XM/bundle.json","state":"https://pith.science/pith/PEXQE5M4ZC3O3G5JWN3CHTF2XM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PEXQE5M4ZC3O3G5JWN3CHTF2XM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PEXQE5M4ZC3O3G5JWN3CHTF2XM","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":"449240f4c64807c3c14f60511ff0b1925a1006743610c8c96b9b506abea08588","cross_cats_sorted":["cs.DS","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:08:21Z","title_canon_sha256":"b22f3ca7b1bd7f1a187e7eeed056a08582c65a1b1caf6e84ae0fe5efe147c9d2"},"schema_version":"1.0","source":{"id":"2408.17165","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.17165","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"arxiv_version","alias_value":"2408.17165v1","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.17165","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_12","alias_value":"PEXQE5M4ZC3O","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_16","alias_value":"PEXQE5M4ZC3O3G5J","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_8","alias_value":"PEXQE5M4","created_at":"2026-07-05T09:01:11Z"}],"graph_snapshots":[{"event_id":"sha256:9b201944fec05caf30d420c89194fd4e3a2ddec62bd918d5bf7f8b9c12be2462","target":"graph","created_at":"2026-07-05T09:01:11Z","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/2408.17165/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study the task of testable learning of general -- not necessarily homogeneous -- halfspaces with adversarial label noise with respect to the Gaussian distribution. In the testable learning framework, the goal is to develop a tester-learner such that if the data passes the tester, then one can trust the output of the robust learner on the data.Our main result is the first polynomial time tester-learner for general halfspaces that achieves dimension-independent misclassification error. At the heart of our approach is a new methodology to reduce testable learning of general halfspaces to testa","authors_text":"Daniel M. Kane, Ilias Diakonikolas, Nikos Zarifis, Sihan Liu","cross_cats":["cs.DS","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:08:21Z","title":"Efficient Testable Learning of General Halfspaces with Adversarial Label Noise"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.17165","kind":"arxiv","version":1},"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":"sha256:53f233ba34e6bfe4d4bc2c92c5f431195e8cb23a06e717ead580787878d52d79","target":"record","created_at":"2026-07-05T09:01:11Z","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":"449240f4c64807c3c14f60511ff0b1925a1006743610c8c96b9b506abea08588","cross_cats_sorted":["cs.DS","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:08:21Z","title_canon_sha256":"b22f3ca7b1bd7f1a187e7eeed056a08582c65a1b1caf6e84ae0fe5efe147c9d2"},"schema_version":"1.0","source":{"id":"2408.17165","kind":"arxiv","version":1}},"canonical_sha256":"792f02759cc8b6ed9ba9b37623ccbabb28b81398d8ffcc46bc46363ae172a70a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"792f02759cc8b6ed9ba9b37623ccbabb28b81398d8ffcc46bc46363ae172a70a","first_computed_at":"2026-07-05T09:01:11.682920Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:01:11.682920Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G4EryxwEMUsXnbZgoK66vAohpJDKFcdqUQykySoMDeX3wqEUh/sdniPPWRtyCKJ+eqY/EarA7rksaYV3zEJDAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:01:11.683397Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.17165","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:53f233ba34e6bfe4d4bc2c92c5f431195e8cb23a06e717ead580787878d52d79","sha256:9b201944fec05caf30d420c89194fd4e3a2ddec62bd918d5bf7f8b9c12be2462"],"state_sha256":"2fe324e422d51055d8f41309c8fa5ab9edecc11da1b4c152b6d2c2ad8fe17e66"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wo0gk3yBjI4sLHxyVbBmbrGkIqjMJk9nLj1wVgsh4nw6kmbFv3Fcln0hDsc26kIQL70vyBGdtMuXT87HIkVfCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T05:10:36.650040Z","bundle_sha256":"8a70d9eb5fa36e9b500467b9edeb0c7f49b3b431df14d021558fa8332395f33e"}}