{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:6T434QUP2A34I5745JF3KHHDCF","short_pith_number":"pith:6T434QUP","canonical_record":{"source":{"id":"1205.4343","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2012-05-19T16:09:15Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c9b8061a344777e4021bdc1f06c8e4f10a7ce222ce3c459bef09098e9f38eb3e","abstract_canon_sha256":"2df3134c7c65cf654fe9789e7beb4e67d91840710b49023ccfcca73ba366f043"},"schema_version":"1.0"},"canonical_sha256":"f4f9be428fd037c477fcea4bb51ce3116181379f709e9708ae9cac4fe17d4f81","source":{"kind":"arxiv","id":"1205.4343","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.4343","created_at":"2026-05-18T03:47:00Z"},{"alias_kind":"arxiv_version","alias_value":"1205.4343v2","created_at":"2026-05-18T03:47:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.4343","created_at":"2026-05-18T03:47:00Z"},{"alias_kind":"pith_short_12","alias_value":"6T434QUP2A34","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"6T434QUP2A34I574","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"6T434QUP","created_at":"2026-05-18T12:26:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:6T434QUP2A34I5745JF3KHHDCF","target":"record","payload":{"canonical_record":{"source":{"id":"1205.4343","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2012-05-19T16:09:15Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c9b8061a344777e4021bdc1f06c8e4f10a7ce222ce3c459bef09098e9f38eb3e","abstract_canon_sha256":"2df3134c7c65cf654fe9789e7beb4e67d91840710b49023ccfcca73ba366f043"},"schema_version":"1.0"},"canonical_sha256":"f4f9be428fd037c477fcea4bb51ce3116181379f709e9708ae9cac4fe17d4f81","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:47:00.832305Z","signature_b64":"aDoxCLMm1XNzkqO1w+ev4mDVeG2cgY+IofOVLCt99KWHTnhMXPYYLSS0UYhFQCQWks2V7yEqfRIlCFn2RSTVCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f4f9be428fd037c477fcea4bb51ce3116181379f709e9708ae9cac4fe17d4f81","last_reissued_at":"2026-05-18T03:47:00.831749Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:47:00.831749Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1205.4343","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:47:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XDrsANxU4aG38oGqLaYxHoXNwnzzxEo0/2Qge0OMszFmj8O/1+U0aMWeCYVT6Bq2Ax2UiiWz7npl6rp+8sX6Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T10:57:06.887963Z"},"content_sha256":"4d93531536687e6f263ddffdb1cebf9ec7b388caaa7bddf93aebf0877298b069","schema_version":"1.0","event_id":"sha256:4d93531536687e6f263ddffdb1cebf9ec7b388caaa7bddf93aebf0877298b069"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:6T434QUP2A34I5745JF3KHHDCF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"New Analysis and Algorithm for Learning with Drifting Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Andres Munoz Medina, Mehryar Mohri","submitted_at":"2012-05-19T16:09:15Z","abstract_excerpt":"We present a new analysis of the problem of learning with drifting distributions in the batch setting using the notion of discrepancy. We prove learning bounds based on the Rademacher complexity of the hypothesis set and the discrepancy of distributions both for a drifting PAC scenario and a tracking scenario. Our bounds are always tighter and in some cases substantially improve upon previous ones based on the $L_1$ distance. We also present a generalization of the standard on-line to batch conversion to the drifting scenario in terms of the discrepancy and arbitrary convex combinations of hyp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.4343","kind":"arxiv","version":2},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:47:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YOeYqu3NzpQ6AdJrFumSjLxBvHcVZYio2pkrcoQnyA14/WABFId0CjSDUo8zu+tDTvNPRWGIM26ke7oSBDRcBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T10:57:06.888309Z"},"content_sha256":"a52cb6ca44a9db656e2c168f4a89f0ebfd85a7305283292e0150383a8ea0da7b","schema_version":"1.0","event_id":"sha256:a52cb6ca44a9db656e2c168f4a89f0ebfd85a7305283292e0150383a8ea0da7b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6T434QUP2A34I5745JF3KHHDCF/bundle.json","state_url":"https://pith.science/pith/6T434QUP2A34I5745JF3KHHDCF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6T434QUP2A34I5745JF3KHHDCF/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":"2026-07-24T10:57:06Z","links":{"resolver":"https://pith.science/pith/6T434QUP2A34I5745JF3KHHDCF","bundle":"https://pith.science/pith/6T434QUP2A34I5745JF3KHHDCF/bundle.json","state":"https://pith.science/pith/6T434QUP2A34I5745JF3KHHDCF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6T434QUP2A34I5745JF3KHHDCF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:6T434QUP2A34I5745JF3KHHDCF","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":"2df3134c7c65cf654fe9789e7beb4e67d91840710b49023ccfcca73ba366f043","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2012-05-19T16:09:15Z","title_canon_sha256":"c9b8061a344777e4021bdc1f06c8e4f10a7ce222ce3c459bef09098e9f38eb3e"},"schema_version":"1.0","source":{"id":"1205.4343","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.4343","created_at":"2026-05-18T03:47:00Z"},{"alias_kind":"arxiv_version","alias_value":"1205.4343v2","created_at":"2026-05-18T03:47:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.4343","created_at":"2026-05-18T03:47:00Z"},{"alias_kind":"pith_short_12","alias_value":"6T434QUP2A34","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"6T434QUP2A34I574","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"6T434QUP","created_at":"2026-05-18T12:26:56Z"}],"graph_snapshots":[{"event_id":"sha256:a52cb6ca44a9db656e2c168f4a89f0ebfd85a7305283292e0150383a8ea0da7b","target":"graph","created_at":"2026-05-18T03:47:00Z","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 a new analysis of the problem of learning with drifting distributions in the batch setting using the notion of discrepancy. We prove learning bounds based on the Rademacher complexity of the hypothesis set and the discrepancy of distributions both for a drifting PAC scenario and a tracking scenario. Our bounds are always tighter and in some cases substantially improve upon previous ones based on the $L_1$ distance. We also present a generalization of the standard on-line to batch conversion to the drifting scenario in terms of the discrepancy and arbitrary convex combinations of hyp","authors_text":"Andres Munoz Medina, Mehryar Mohri","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2012-05-19T16:09:15Z","title":"New Analysis and Algorithm for Learning with Drifting Distributions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.4343","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":"sha256:4d93531536687e6f263ddffdb1cebf9ec7b388caaa7bddf93aebf0877298b069","target":"record","created_at":"2026-05-18T03:47:00Z","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":"2df3134c7c65cf654fe9789e7beb4e67d91840710b49023ccfcca73ba366f043","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2012-05-19T16:09:15Z","title_canon_sha256":"c9b8061a344777e4021bdc1f06c8e4f10a7ce222ce3c459bef09098e9f38eb3e"},"schema_version":"1.0","source":{"id":"1205.4343","kind":"arxiv","version":2}},"canonical_sha256":"f4f9be428fd037c477fcea4bb51ce3116181379f709e9708ae9cac4fe17d4f81","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f4f9be428fd037c477fcea4bb51ce3116181379f709e9708ae9cac4fe17d4f81","first_computed_at":"2026-05-18T03:47:00.831749Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:47:00.831749Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aDoxCLMm1XNzkqO1w+ev4mDVeG2cgY+IofOVLCt99KWHTnhMXPYYLSS0UYhFQCQWks2V7yEqfRIlCFn2RSTVCg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:47:00.832305Z","signed_message":"canonical_sha256_bytes"},"source_id":"1205.4343","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4d93531536687e6f263ddffdb1cebf9ec7b388caaa7bddf93aebf0877298b069","sha256:a52cb6ca44a9db656e2c168f4a89f0ebfd85a7305283292e0150383a8ea0da7b"],"state_sha256":"6d6b352b5101cbffe377c236694c1846bb85f80da389ced0487c32b5f8be5cca"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WWn+dilqVJPP0hT/a3gOZ3hsxImZK0y4nguiGDF0SKl1rjdi+4zoZtCdyUvBxy7p1Y1Lav1QUBqOqSxovcuLDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-24T10:57:06.890533Z","bundle_sha256":"4934087f2b126012dc0c13132e1ad6bb6599d4244c03ee5fa40ee7c87a50761d"}}