{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:XQIJSMP2IBNE35S43QCRLGTZPQ","short_pith_number":"pith:XQIJSMP2","canonical_record":{"source":{"id":"1907.11826","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-07-27T01:42:29Z","cross_cats_sorted":["cs.LG","stat.CO"],"title_canon_sha256":"5574e732f1baeae2bc0ac4705a39e1012a348c10d0c36e343a353aca5689f89b","abstract_canon_sha256":"9598d2ee6e20d9a213fb0f3618b68dadda969f3c083256847156d15b2f9364fa"},"schema_version":"1.0"},"canonical_sha256":"bc109931fa405a4df65cdc05159a797c129e7052fbb8a74472476222a35fdf91","source":{"kind":"arxiv","id":"1907.11826","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11826","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11826v1","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11826","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"pith_short_12","alias_value":"XQIJSMP2IBNE","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"XQIJSMP2IBNE35S4","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"XQIJSMP2","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:XQIJSMP2IBNE35S43QCRLGTZPQ","target":"record","payload":{"canonical_record":{"source":{"id":"1907.11826","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-07-27T01:42:29Z","cross_cats_sorted":["cs.LG","stat.CO"],"title_canon_sha256":"5574e732f1baeae2bc0ac4705a39e1012a348c10d0c36e343a353aca5689f89b","abstract_canon_sha256":"9598d2ee6e20d9a213fb0f3618b68dadda969f3c083256847156d15b2f9364fa"},"schema_version":"1.0"},"canonical_sha256":"bc109931fa405a4df65cdc05159a797c129e7052fbb8a74472476222a35fdf91","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:22.961553Z","signature_b64":"vsdC5nNYjzXeJXaSQ4djnBjKwOJnuTx1AGZpUeH4HYlJ/3g0bQ/kRP6Bxy6Nlj6KS/3t74LtGzCVB6NZ18qIAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc109931fa405a4df65cdc05159a797c129e7052fbb8a74472476222a35fdf91","last_reissued_at":"2026-05-17T23:39:22.960791Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:22.960791Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.11826","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":"2026-05-17T23:39:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bxb5Ql7drYZwxHnBxzDmVKDSIk+X21wo8vLtKLpkh5xCDmlI5LrECn9g+BHqek1+3RATwA5pyMueHJ+E56WcAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T00:56:31.576574Z"},"content_sha256":"3e2b7dd6c77854725ab803a325644e7213c9f33b7b07d0d87d411ae96dd1b4fc","schema_version":"1.0","event_id":"sha256:3e2b7dd6c77854725ab803a325644e7213c9f33b7b07d0d87d411ae96dd1b4fc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:XQIJSMP2IBNE35S43QCRLGTZPQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Robustness: A Nonasymptotic Viewpoint","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.CO"],"primary_cat":"stat.ML","authors_text":"Anca D. Dragan, Kush Bhatia, Michael I. Jordan, Peter L. Bartlett, Yi-An Ma","submitted_at":"2019-07-27T01:42:29Z","abstract_excerpt":"We study the problem of robustly estimating the posterior distribution for the setting where observed data can be contaminated with potentially adversarial outliers. We propose Rob-ULA, a robust variant of the Unadjusted Langevin Algorithm (ULA), and provide a finite-sample analysis of its sampling distribution. In particular, we show that after $T= \\tilde{\\mathcal{O}}(d/\\varepsilon_{\\textsf{acc}})$ iterations, we can sample from $p_T$ such that $\\text{dist}(p_T, p^*) \\leq \\varepsilon_{\\textsf{acc}} + \\tilde{\\mathcal{O}}(\\epsilon)$, where $\\epsilon$ is the fraction of corruptions. We corrobora"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11826","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":""},"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":"2026-05-17T23:39:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NPRAlPB0hHVdbX/HLMHnyvIAqBjmKGqapjk1w0UiGBWznM9qx+q0n733/sUoIJGoNSajLZuj5KWdBYz4ib7CDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T00:56:31.576929Z"},"content_sha256":"1210aa86bdc3f401c6d6f2000174a5c03476d6c16d130d8f2b6407c369edf296","schema_version":"1.0","event_id":"sha256:1210aa86bdc3f401c6d6f2000174a5c03476d6c16d130d8f2b6407c369edf296"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XQIJSMP2IBNE35S43QCRLGTZPQ/bundle.json","state_url":"https://pith.science/pith/XQIJSMP2IBNE35S43QCRLGTZPQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XQIJSMP2IBNE35S43QCRLGTZPQ/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":"2026-06-03T00:56:31Z","links":{"resolver":"https://pith.science/pith/XQIJSMP2IBNE35S43QCRLGTZPQ","bundle":"https://pith.science/pith/XQIJSMP2IBNE35S43QCRLGTZPQ/bundle.json","state":"https://pith.science/pith/XQIJSMP2IBNE35S43QCRLGTZPQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XQIJSMP2IBNE35S43QCRLGTZPQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:XQIJSMP2IBNE35S43QCRLGTZPQ","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":"9598d2ee6e20d9a213fb0f3618b68dadda969f3c083256847156d15b2f9364fa","cross_cats_sorted":["cs.LG","stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-07-27T01:42:29Z","title_canon_sha256":"5574e732f1baeae2bc0ac4705a39e1012a348c10d0c36e343a353aca5689f89b"},"schema_version":"1.0","source":{"id":"1907.11826","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11826","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11826v1","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11826","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"pith_short_12","alias_value":"XQIJSMP2IBNE","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"XQIJSMP2IBNE35S4","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"XQIJSMP2","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:1210aa86bdc3f401c6d6f2000174a5c03476d6c16d130d8f2b6407c369edf296","target":"graph","created_at":"2026-05-17T23:39:22Z","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 study the problem of robustly estimating the posterior distribution for the setting where observed data can be contaminated with potentially adversarial outliers. We propose Rob-ULA, a robust variant of the Unadjusted Langevin Algorithm (ULA), and provide a finite-sample analysis of its sampling distribution. In particular, we show that after $T= \\tilde{\\mathcal{O}}(d/\\varepsilon_{\\textsf{acc}})$ iterations, we can sample from $p_T$ such that $\\text{dist}(p_T, p^*) \\leq \\varepsilon_{\\textsf{acc}} + \\tilde{\\mathcal{O}}(\\epsilon)$, where $\\epsilon$ is the fraction of corruptions. We corrobora","authors_text":"Anca D. Dragan, Kush Bhatia, Michael I. Jordan, Peter L. Bartlett, Yi-An Ma","cross_cats":["cs.LG","stat.CO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-07-27T01:42:29Z","title":"Bayesian Robustness: A Nonasymptotic Viewpoint"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11826","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":"sha256:3e2b7dd6c77854725ab803a325644e7213c9f33b7b07d0d87d411ae96dd1b4fc","target":"record","created_at":"2026-05-17T23:39:22Z","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":"9598d2ee6e20d9a213fb0f3618b68dadda969f3c083256847156d15b2f9364fa","cross_cats_sorted":["cs.LG","stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-07-27T01:42:29Z","title_canon_sha256":"5574e732f1baeae2bc0ac4705a39e1012a348c10d0c36e343a353aca5689f89b"},"schema_version":"1.0","source":{"id":"1907.11826","kind":"arxiv","version":1}},"canonical_sha256":"bc109931fa405a4df65cdc05159a797c129e7052fbb8a74472476222a35fdf91","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc109931fa405a4df65cdc05159a797c129e7052fbb8a74472476222a35fdf91","first_computed_at":"2026-05-17T23:39:22.960791Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:22.960791Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vsdC5nNYjzXeJXaSQ4djnBjKwOJnuTx1AGZpUeH4HYlJ/3g0bQ/kRP6Bxy6Nlj6KS/3t74LtGzCVB6NZ18qIAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:22.961553Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.11826","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e2b7dd6c77854725ab803a325644e7213c9f33b7b07d0d87d411ae96dd1b4fc","sha256:1210aa86bdc3f401c6d6f2000174a5c03476d6c16d130d8f2b6407c369edf296"],"state_sha256":"489b0944e1abff27482fa588c7af1e7dec5904bafc56215dd23b080901564dc9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U/BwcDILSHb9uMKPS0s25k4TPvRpgTBPKgnfm/KmmKVew32MhdGaiqlunIt8l5yf0FLBjlZsNI8e3Vt9Vz70DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T00:56:31.578921Z","bundle_sha256":"65f239e518f2afede9d02affb0b66fdb674f6775defe8c8a04dc0d20b102d0b4"}}