{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:IAGSX6PH43BWLRHMGGFHOTA2SW","short_pith_number":"pith:IAGSX6PH","canonical_record":{"source":{"id":"1504.00091","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2015-04-01T02:54:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"82752614d2414dee783109112fdc1b48b68c0bfa12aacc84c4200e123b0ad96c","abstract_canon_sha256":"328de95b7455b9d82d3c6e84ff40b5ff0594833b6c3af2aead2ad306dffcfda8"},"schema_version":"1.0"},"canonical_sha256":"400d2bf9e7e6c365c4ec318a774c1a9586defbb0a422defce00a28dda8a78577","source":{"kind":"arxiv","id":"1504.00091","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1504.00091","created_at":"2026-05-18T01:37:18Z"},{"alias_kind":"arxiv_version","alias_value":"1504.00091v2","created_at":"2026-05-18T01:37:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1504.00091","created_at":"2026-05-18T01:37:18Z"},{"alias_kind":"pith_short_12","alias_value":"IAGSX6PH43BW","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_16","alias_value":"IAGSX6PH43BWLRHM","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_8","alias_value":"IAGSX6PH","created_at":"2026-05-18T12:29:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:IAGSX6PH43BWLRHMGGFHOTA2SW","target":"record","payload":{"canonical_record":{"source":{"id":"1504.00091","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2015-04-01T02:54:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"82752614d2414dee783109112fdc1b48b68c0bfa12aacc84c4200e123b0ad96c","abstract_canon_sha256":"328de95b7455b9d82d3c6e84ff40b5ff0594833b6c3af2aead2ad306dffcfda8"},"schema_version":"1.0"},"canonical_sha256":"400d2bf9e7e6c365c4ec318a774c1a9586defbb0a422defce00a28dda8a78577","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:37:18.890209Z","signature_b64":"uEoBbUEQCuzI986kLJ+nlQCTRB/8x8OklFiiQulr8XzwHrjwpYkqBKyL1R7WmzP4WrRcFYpZMgfxoBYt3sgxCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"400d2bf9e7e6c365c4ec318a774c1a9586defbb0a422defce00a28dda8a78577","last_reissued_at":"2026-05-18T01:37:18.889473Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:37:18.889473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1504.00091","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":"2026-05-18T01:37:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HOb+ieZwIUhP63CSscBxWGziN/23o/srH6FXSjka30vultai6vtMpMy2BXBH8sgQdLrlZmk6VgEFF5G8XbyxCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:58:14.881116Z"},"content_sha256":"2ce9a9e555623d762efdba3956ebfe083e26f64d8f213cc39a1b027ee92c78bd","schema_version":"1.0","event_id":"sha256:2ce9a9e555623d762efdba3956ebfe083e26f64d8f213cc39a1b027ee92c78bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:IAGSX6PH43BWLRHMGGFHOTA2SW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning in the Presence of Corruption","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Brendan van Rooyen, Robert C. Williamson","submitted_at":"2015-04-01T02:54:38Z","abstract_excerpt":"In supervised learning one wishes to identify a pattern present in a joint distribution $P$, of instances, label pairs, by providing a function $f$ from instances to labels that has low risk $\\mathbb{E}_{P}\\ell(y,f(x))$. To do so, the learner is given access to $n$ iid samples drawn from $P$. In many real world problems clean samples are not available. Rather, the learner is given access to samples from a corrupted distribution $\\tilde{P}$ from which to learn, while the goal of predicting the clean pattern remains. There are many different types of corruption one can consider, and as of yet th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1504.00091","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":"2026-05-18T01:37:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PRJCTWq94nbCK1TFAHQNpLkaYA/ZItbTDhZSBLsPltSL047gl5iXZ9Y2Mu+ttqCkogP1QzirnoUvutADztaxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:58:14.881628Z"},"content_sha256":"d0c179abd3a26860396734d1a606ce32712e219fa98176600e7e84fcca595e22","schema_version":"1.0","event_id":"sha256:d0c179abd3a26860396734d1a606ce32712e219fa98176600e7e84fcca595e22"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IAGSX6PH43BWLRHMGGFHOTA2SW/bundle.json","state_url":"https://pith.science/pith/IAGSX6PH43BWLRHMGGFHOTA2SW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IAGSX6PH43BWLRHMGGFHOTA2SW/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":"2026-05-26T15:58:14Z","links":{"resolver":"https://pith.science/pith/IAGSX6PH43BWLRHMGGFHOTA2SW","bundle":"https://pith.science/pith/IAGSX6PH43BWLRHMGGFHOTA2SW/bundle.json","state":"https://pith.science/pith/IAGSX6PH43BWLRHMGGFHOTA2SW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IAGSX6PH43BWLRHMGGFHOTA2SW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:IAGSX6PH43BWLRHMGGFHOTA2SW","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":"328de95b7455b9d82d3c6e84ff40b5ff0594833b6c3af2aead2ad306dffcfda8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2015-04-01T02:54:38Z","title_canon_sha256":"82752614d2414dee783109112fdc1b48b68c0bfa12aacc84c4200e123b0ad96c"},"schema_version":"1.0","source":{"id":"1504.00091","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1504.00091","created_at":"2026-05-18T01:37:18Z"},{"alias_kind":"arxiv_version","alias_value":"1504.00091v2","created_at":"2026-05-18T01:37:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1504.00091","created_at":"2026-05-18T01:37:18Z"},{"alias_kind":"pith_short_12","alias_value":"IAGSX6PH43BW","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_16","alias_value":"IAGSX6PH43BWLRHM","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_8","alias_value":"IAGSX6PH","created_at":"2026-05-18T12:29:25Z"}],"graph_snapshots":[{"event_id":"sha256:d0c179abd3a26860396734d1a606ce32712e219fa98176600e7e84fcca595e22","target":"graph","created_at":"2026-05-18T01:37:18Z","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":"In supervised learning one wishes to identify a pattern present in a joint distribution $P$, of instances, label pairs, by providing a function $f$ from instances to labels that has low risk $\\mathbb{E}_{P}\\ell(y,f(x))$. To do so, the learner is given access to $n$ iid samples drawn from $P$. In many real world problems clean samples are not available. Rather, the learner is given access to samples from a corrupted distribution $\\tilde{P}$ from which to learn, while the goal of predicting the clean pattern remains. There are many different types of corruption one can consider, and as of yet th","authors_text":"Brendan van Rooyen, Robert C. Williamson","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2015-04-01T02:54:38Z","title":"Learning in the Presence of Corruption"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1504.00091","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":"sha256:2ce9a9e555623d762efdba3956ebfe083e26f64d8f213cc39a1b027ee92c78bd","target":"record","created_at":"2026-05-18T01:37:18Z","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":"328de95b7455b9d82d3c6e84ff40b5ff0594833b6c3af2aead2ad306dffcfda8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2015-04-01T02:54:38Z","title_canon_sha256":"82752614d2414dee783109112fdc1b48b68c0bfa12aacc84c4200e123b0ad96c"},"schema_version":"1.0","source":{"id":"1504.00091","kind":"arxiv","version":2}},"canonical_sha256":"400d2bf9e7e6c365c4ec318a774c1a9586defbb0a422defce00a28dda8a78577","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"400d2bf9e7e6c365c4ec318a774c1a9586defbb0a422defce00a28dda8a78577","first_computed_at":"2026-05-18T01:37:18.889473Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:37:18.889473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uEoBbUEQCuzI986kLJ+nlQCTRB/8x8OklFiiQulr8XzwHrjwpYkqBKyL1R7WmzP4WrRcFYpZMgfxoBYt3sgxCw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:37:18.890209Z","signed_message":"canonical_sha256_bytes"},"source_id":"1504.00091","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2ce9a9e555623d762efdba3956ebfe083e26f64d8f213cc39a1b027ee92c78bd","sha256:d0c179abd3a26860396734d1a606ce32712e219fa98176600e7e84fcca595e22"],"state_sha256":"f4c75598bcc3c592f7f7e4f3bcd9ff2aadace29fdaae006348b46b1041b64c1c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DzOzCjxnozEO9i4rk6lK0cvw0bZZ4ls0fTzOySfgEo/NbcWevRO/X3FJEOe/nFFtt+yiJBCL/od8zzXm71vaAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T15:58:14.884770Z","bundle_sha256":"a523495a80a90d8d1d0ec3a355457a7d07a3f3a9176902d5e1a97b416de27b5f"}}