{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:Y4ENVOGPGI47OTF2QDLVZ3YTZY","short_pith_number":"pith:Y4ENVOGP","canonical_record":{"source":{"id":"2206.05199","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-10T15:57:18Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"81c65cb132550ed0f164347e212b0fb36c8277fe5b42ab81c6e41d0ff449a70e","abstract_canon_sha256":"766105ce8866f9984c548511d42d1cfd004c91f1443e7feae77f16377c69e1f9"},"schema_version":"1.0"},"canonical_sha256":"c708dab8cf3239f74cba80d75cef13ce0c04e0453c70b587009fc465a097e9d0","source":{"kind":"arxiv","id":"2206.05199","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.05199","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"arxiv_version","alias_value":"2206.05199v2","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.05199","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"pith_short_12","alias_value":"Y4ENVOGPGI47","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"pith_short_16","alias_value":"Y4ENVOGPGI47OTF2","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"pith_short_8","alias_value":"Y4ENVOGP","created_at":"2026-07-05T04:32:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:Y4ENVOGPGI47OTF2QDLVZ3YTZY","target":"record","payload":{"canonical_record":{"source":{"id":"2206.05199","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-10T15:57:18Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"81c65cb132550ed0f164347e212b0fb36c8277fe5b42ab81c6e41d0ff449a70e","abstract_canon_sha256":"766105ce8866f9984c548511d42d1cfd004c91f1443e7feae77f16377c69e1f9"},"schema_version":"1.0"},"canonical_sha256":"c708dab8cf3239f74cba80d75cef13ce0c04e0453c70b587009fc465a097e9d0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:32:01.315852Z","signature_b64":"ZehDFDgGUzZOMoYZ8dCaLvn/fMqh91fymBIrj05cVp/puvvsdqINNImJklXlfG/WwC0UUXAty1YbZpnLI260CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c708dab8cf3239f74cba80d75cef13ce0c04e0453c70b587009fc465a097e9d0","last_reissued_at":"2026-07-05T04:32:01.315367Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:32:01.315367Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.05199","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":"2026-07-05T04:32:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BVb9cHM5dAkFFQU58GlFakh72pEvbyEFik5mXkjH17CF+rp1Rl9lI/qFCsIXrIdqZuKrjPIfVFwjHWcuee6nCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T07:56:37.664405Z"},"content_sha256":"36cc3e89f02f348c83913c7fe198231632ed8d4b7fa6ba5adb542b423b841a69","schema_version":"1.0","event_id":"sha256:36cc3e89f02f348c83913c7fe198231632ed8d4b7fa6ba5adb542b423b841a69"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:Y4ENVOGPGI47OTF2QDLVZ3YTZY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Estimation of Differential Privacy","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Ahmed Salem (Microsoft Research), Andrew Paverd (Microsoft Research), Boris K\\\"opf (Microsoft Research), Daniel Jones (Microsoft), Lukas Wutschitz (Microsoft), Mohammad Naseri (University College London), Santiago Zanella-B\\'eguelin (Microsoft Research), Shruti Tople (Microsoft Research), Victor R\\\"uhle (Microsoft)","submitted_at":"2022-06-10T15:57:18Z","abstract_excerpt":"Algorithms such as Differentially Private SGD enable training machine learning models with formal privacy guarantees. However, there is a discrepancy between the protection that such algorithms guarantee in theory and the protection they afford in practice. An emerging strand of work empirically estimates the protection afforded by differentially private training as a confidence interval for the privacy budget $\\varepsilon$ spent on training a model. Existing approaches derive confidence intervals for $\\varepsilon$ from confidence intervals for the false positive and false negative rates of me"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.05199","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2206.05199/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":"2026-07-05T04:32:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DSWT+UFlv0rZHHQQuGmMN26O9c5jNFu9aoSktdH1iNeG+Xw+ocdXAbn5vAhCDejD5mOgYEMa4S5mQB3a80LKCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T07:56:37.664791Z"},"content_sha256":"b3a63312121fab4c039a5661c54318b6c01225310297b147f70af0c686eeb2d8","schema_version":"1.0","event_id":"sha256:b3a63312121fab4c039a5661c54318b6c01225310297b147f70af0c686eeb2d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y4ENVOGPGI47OTF2QDLVZ3YTZY/bundle.json","state_url":"https://pith.science/pith/Y4ENVOGPGI47OTF2QDLVZ3YTZY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y4ENVOGPGI47OTF2QDLVZ3YTZY/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":"2026-07-06T07:56:37Z","links":{"resolver":"https://pith.science/pith/Y4ENVOGPGI47OTF2QDLVZ3YTZY","bundle":"https://pith.science/pith/Y4ENVOGPGI47OTF2QDLVZ3YTZY/bundle.json","state":"https://pith.science/pith/Y4ENVOGPGI47OTF2QDLVZ3YTZY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y4ENVOGPGI47OTF2QDLVZ3YTZY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:Y4ENVOGPGI47OTF2QDLVZ3YTZY","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":"766105ce8866f9984c548511d42d1cfd004c91f1443e7feae77f16377c69e1f9","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-10T15:57:18Z","title_canon_sha256":"81c65cb132550ed0f164347e212b0fb36c8277fe5b42ab81c6e41d0ff449a70e"},"schema_version":"1.0","source":{"id":"2206.05199","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.05199","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"arxiv_version","alias_value":"2206.05199v2","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.05199","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"pith_short_12","alias_value":"Y4ENVOGPGI47","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"pith_short_16","alias_value":"Y4ENVOGPGI47OTF2","created_at":"2026-07-05T04:32:01Z"},{"alias_kind":"pith_short_8","alias_value":"Y4ENVOGP","created_at":"2026-07-05T04:32:01Z"}],"graph_snapshots":[{"event_id":"sha256:b3a63312121fab4c039a5661c54318b6c01225310297b147f70af0c686eeb2d8","target":"graph","created_at":"2026-07-05T04:32:01Z","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/2206.05199/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Algorithms such as Differentially Private SGD enable training machine learning models with formal privacy guarantees. However, there is a discrepancy between the protection that such algorithms guarantee in theory and the protection they afford in practice. An emerging strand of work empirically estimates the protection afforded by differentially private training as a confidence interval for the privacy budget $\\varepsilon$ spent on training a model. Existing approaches derive confidence intervals for $\\varepsilon$ from confidence intervals for the false positive and false negative rates of me","authors_text":"Ahmed Salem (Microsoft Research), Andrew Paverd (Microsoft Research), Boris K\\\"opf (Microsoft Research), Daniel Jones (Microsoft), Lukas Wutschitz (Microsoft), Mohammad Naseri (University College London), Santiago Zanella-B\\'eguelin (Microsoft Research), Shruti Tople (Microsoft Research), Victor R\\\"uhle (Microsoft)","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-10T15:57:18Z","title":"Bayesian Estimation of Differential Privacy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.05199","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":"sha256:36cc3e89f02f348c83913c7fe198231632ed8d4b7fa6ba5adb542b423b841a69","target":"record","created_at":"2026-07-05T04:32:01Z","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":"766105ce8866f9984c548511d42d1cfd004c91f1443e7feae77f16377c69e1f9","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-10T15:57:18Z","title_canon_sha256":"81c65cb132550ed0f164347e212b0fb36c8277fe5b42ab81c6e41d0ff449a70e"},"schema_version":"1.0","source":{"id":"2206.05199","kind":"arxiv","version":2}},"canonical_sha256":"c708dab8cf3239f74cba80d75cef13ce0c04e0453c70b587009fc465a097e9d0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c708dab8cf3239f74cba80d75cef13ce0c04e0453c70b587009fc465a097e9d0","first_computed_at":"2026-07-05T04:32:01.315367Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:32:01.315367Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZehDFDgGUzZOMoYZ8dCaLvn/fMqh91fymBIrj05cVp/puvvsdqINNImJklXlfG/WwC0UUXAty1YbZpnLI260CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:32:01.315852Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.05199","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:36cc3e89f02f348c83913c7fe198231632ed8d4b7fa6ba5adb542b423b841a69","sha256:b3a63312121fab4c039a5661c54318b6c01225310297b147f70af0c686eeb2d8"],"state_sha256":"305d6173f7aa16a2c5dff49990d13ed0fcfa96e6b42d2f4dad537dc5fc976002"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/jY0suRFi6d80d5CCpkSbziLUW9M2kITXrEZt5Lwy7hsfZCHQxtxfv941zzvCildu6CrBU5DXh7MSwSJqTLpAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T07:56:37.667257Z","bundle_sha256":"f4dfabfefb606bf47f63c1a5a3114e66113e619399b855c1856e2dedc96be209"}}