{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:EJTPBZETHFN5ELKYKXX4GOELYQ","short_pith_number":"pith:EJTPBZET","canonical_record":{"source":{"id":"2202.10517","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-21T20:16:27Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"256cd008f813e7c2473bd1b0a0297a2880885d6198f679047cc207fbea0111b6","abstract_canon_sha256":"923ab71253b71fc73312c8d5fb6e7d73e8d348fe6bc8100304f0a5f276b650a3"},"schema_version":"1.0"},"canonical_sha256":"2266f0e493395bd22d5855efc3388bc42ccd4b5d3810b91131bdb503a736ae94","source":{"kind":"arxiv","id":"2202.10517","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.10517","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"arxiv_version","alias_value":"2202.10517v4","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.10517","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"pith_short_12","alias_value":"EJTPBZETHFN5","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"pith_short_16","alias_value":"EJTPBZETHFN5ELKY","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"pith_short_8","alias_value":"EJTPBZET","created_at":"2026-07-05T05:14:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:EJTPBZETHFN5ELKYKXX4GOELYQ","target":"record","payload":{"canonical_record":{"source":{"id":"2202.10517","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-21T20:16:27Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"256cd008f813e7c2473bd1b0a0297a2880885d6198f679047cc207fbea0111b6","abstract_canon_sha256":"923ab71253b71fc73312c8d5fb6e7d73e8d348fe6bc8100304f0a5f276b650a3"},"schema_version":"1.0"},"canonical_sha256":"2266f0e493395bd22d5855efc3388bc42ccd4b5d3810b91131bdb503a736ae94","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:14:11.321564Z","signature_b64":"JAN+CSOdME+km3wbcSB7pHJF9dx7vhwVciessJ44IyzURdC/J1Gy3i9J0IQQjg0jEeQmTSkyLY9p/f4j/WvSAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2266f0e493395bd22d5855efc3388bc42ccd4b5d3810b91131bdb503a736ae94","last_reissued_at":"2026-07-05T05:14:11.320953Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:14:11.320953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.10517","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:14:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dkwuk2OlvXkZKsWck4ODDGWDhkjC9y4QL5wdEthSqSkEhEn3ZWcv4E5ccgSeJ9b3hgqmb8AUhwovZ6Lkwjf7Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:08:59.653687Z"},"content_sha256":"528a77d4485c8e7c4c558812e25eab38616fb604ed7f66b1093c6808e09c1ce7","schema_version":"1.0","event_id":"sha256:528a77d4485c8e7c4c558812e25eab38616fb604ed7f66b1093c6808e09c1ce7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:EJTPBZETHFN5ELKYKXX4GOELYQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Adam Dziedzic, Christopher M\\\"uhl, Franziska Boenisch, Jannis Ihrig, Roy Rinberg","submitted_at":"2022-02-21T20:16:27Z","abstract_excerpt":"Applying machine learning (ML) to sensitive domains requires privacy protection of the underlying training data through formal privacy frameworks, such as differential privacy (DP). Yet, usually, the privacy of the training data comes at the cost of the resulting ML models' utility. One reason for this is that DP uses one uniform privacy budget epsilon for all training data points, which has to align with the strictest privacy requirement encountered among all data holders. In practice, different data holders have different privacy requirements and data points of data holders with lower requir"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.10517","kind":"arxiv","version":4},"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/2202.10517/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":"2026-07-05T05:14:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ROJ4nOnE7uLcyMuTHIPlZ0OQ/yRhY4wA/re68+KxU4If3+WFwGi/VFe/odGprOaOpm+kIG3leNMqV2YNFJ8mDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:08:59.654207Z"},"content_sha256":"963547d323196956a7651ac4764d12ffb4a53fc681cf1961b5b9b35ae5c9be22","schema_version":"1.0","event_id":"sha256:963547d323196956a7651ac4764d12ffb4a53fc681cf1961b5b9b35ae5c9be22"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EJTPBZETHFN5ELKYKXX4GOELYQ/bundle.json","state_url":"https://pith.science/pith/EJTPBZETHFN5ELKYKXX4GOELYQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EJTPBZETHFN5ELKYKXX4GOELYQ/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":"2026-08-05T06:08:59Z","links":{"resolver":"https://pith.science/pith/EJTPBZETHFN5ELKYKXX4GOELYQ","bundle":"https://pith.science/pith/EJTPBZETHFN5ELKYKXX4GOELYQ/bundle.json","state":"https://pith.science/pith/EJTPBZETHFN5ELKYKXX4GOELYQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EJTPBZETHFN5ELKYKXX4GOELYQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EJTPBZETHFN5ELKYKXX4GOELYQ","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":"923ab71253b71fc73312c8d5fb6e7d73e8d348fe6bc8100304f0a5f276b650a3","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-21T20:16:27Z","title_canon_sha256":"256cd008f813e7c2473bd1b0a0297a2880885d6198f679047cc207fbea0111b6"},"schema_version":"1.0","source":{"id":"2202.10517","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.10517","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"arxiv_version","alias_value":"2202.10517v4","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.10517","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"pith_short_12","alias_value":"EJTPBZETHFN5","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"pith_short_16","alias_value":"EJTPBZETHFN5ELKY","created_at":"2026-07-05T05:14:11Z"},{"alias_kind":"pith_short_8","alias_value":"EJTPBZET","created_at":"2026-07-05T05:14:11Z"}],"graph_snapshots":[{"event_id":"sha256:963547d323196956a7651ac4764d12ffb4a53fc681cf1961b5b9b35ae5c9be22","target":"graph","created_at":"2026-07-05T05:14:11Z","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/2202.10517/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Applying machine learning (ML) to sensitive domains requires privacy protection of the underlying training data through formal privacy frameworks, such as differential privacy (DP). Yet, usually, the privacy of the training data comes at the cost of the resulting ML models' utility. One reason for this is that DP uses one uniform privacy budget epsilon for all training data points, which has to align with the strictest privacy requirement encountered among all data holders. In practice, different data holders have different privacy requirements and data points of data holders with lower requir","authors_text":"Adam Dziedzic, Christopher M\\\"uhl, Franziska Boenisch, Jannis Ihrig, Roy Rinberg","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-21T20:16:27Z","title":"Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.10517","kind":"arxiv","version":4},"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":"sha256:528a77d4485c8e7c4c558812e25eab38616fb604ed7f66b1093c6808e09c1ce7","target":"record","created_at":"2026-07-05T05:14:11Z","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":"923ab71253b71fc73312c8d5fb6e7d73e8d348fe6bc8100304f0a5f276b650a3","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-21T20:16:27Z","title_canon_sha256":"256cd008f813e7c2473bd1b0a0297a2880885d6198f679047cc207fbea0111b6"},"schema_version":"1.0","source":{"id":"2202.10517","kind":"arxiv","version":4}},"canonical_sha256":"2266f0e493395bd22d5855efc3388bc42ccd4b5d3810b91131bdb503a736ae94","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2266f0e493395bd22d5855efc3388bc42ccd4b5d3810b91131bdb503a736ae94","first_computed_at":"2026-07-05T05:14:11.320953Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:14:11.320953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JAN+CSOdME+km3wbcSB7pHJF9dx7vhwVciessJ44IyzURdC/J1Gy3i9J0IQQjg0jEeQmTSkyLY9p/f4j/WvSAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:14:11.321564Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.10517","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:528a77d4485c8e7c4c558812e25eab38616fb604ed7f66b1093c6808e09c1ce7","sha256:963547d323196956a7651ac4764d12ffb4a53fc681cf1961b5b9b35ae5c9be22"],"state_sha256":"f6a72f4bb9a810b5e0c5048c8c0b47f64eea303bb96e243f7dda6540087d4236"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eMw8XVgb3AKRkVEr9MzZ1sPF2iovkDgZ/kqzXBINGf9OAu6IUxznBMAl21G8Y/brNOP3YU4ZY6E83OgH1LyCCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T06:08:59.659094Z","bundle_sha256":"a81c70a16c31b6ded3cf625063af7fa64dc179892e0a289e4b2047d96900453b"}}