{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SB6EOUGV7FTNT6ZHC66LXVTIQD","short_pith_number":"pith:SB6EOUGV","canonical_record":{"source":{"id":"2406.06749","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-06-10T19:25:19Z","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"title_canon_sha256":"573a7b8f5345226b8f1b0a4aa2e9ed44ddfa7e081a3c31a71a6621cc7ac442a7","abstract_canon_sha256":"0b4398fbd8bbec54a8f71751f755064f30478767847101e720d1a3d3c324459a"},"schema_version":"1.0"},"canonical_sha256":"907c4750d5f966d9fb2717bcbbd66880d4c2b8240f90370bbe589faa58824d8c","source":{"kind":"arxiv","id":"2406.06749","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.06749","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"arxiv_version","alias_value":"2406.06749v1","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.06749","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"pith_short_12","alias_value":"SB6EOUGV7FTN","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"pith_short_16","alias_value":"SB6EOUGV7FTNT6ZH","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"pith_short_8","alias_value":"SB6EOUGV","created_at":"2026-07-05T08:29:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SB6EOUGV7FTNT6ZHC66LXVTIQD","target":"record","payload":{"canonical_record":{"source":{"id":"2406.06749","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-06-10T19:25:19Z","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"title_canon_sha256":"573a7b8f5345226b8f1b0a4aa2e9ed44ddfa7e081a3c31a71a6621cc7ac442a7","abstract_canon_sha256":"0b4398fbd8bbec54a8f71751f755064f30478767847101e720d1a3d3c324459a"},"schema_version":"1.0"},"canonical_sha256":"907c4750d5f966d9fb2717bcbbd66880d4c2b8240f90370bbe589faa58824d8c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:29:49.583203Z","signature_b64":"Pt1Hkj5fcpdDgpvuC2GdxiKbZ4dZBEx02Ub/4rULlYQv3JAAY3pVE0K57iCoIxvYv9/89H5kIxz14X3eXk/mBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"907c4750d5f966d9fb2717bcbbd66880d4c2b8240f90370bbe589faa58824d8c","last_reissued_at":"2026-07-05T08:29:49.582820Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:29:49.582820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.06749","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":"2026-07-05T08:29:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NVLlXVDTo2eM3LS6GOy7M080naO8GmZaHkxJ05PHcYBf1XK4X1zTHePatvkTHVa0dOijDt/vK77ZZUGFL1P1CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T02:18:38.957443Z"},"content_sha256":"58048220e337c21b39d5e1a682ca10ba1bdc10608d7e7d3372872d912ab5dcce","schema_version":"1.0","event_id":"sha256:58048220e337c21b39d5e1a682ca10ba1bdc10608d7e7d3372872d912ab5dcce"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SB6EOUGV7FTNT6ZHC66LXVTIQD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","stat.ML","stat.TH"],"primary_cat":"math.ST","authors_text":"Abhinav Chakraborty, Lasse Vuursteen, T. Tony Cai","submitted_at":"2024-06-10T19:25:19Z","abstract_excerpt":"Federated learning has attracted significant recent attention due to its applicability across a wide range of settings where data is collected and analyzed across disparate locations. In this paper, we study federated nonparametric goodness-of-fit testing in the white-noise-with-drift model under distributed differential privacy (DP) constraints.\n  We first establish matching lower and upper bounds, up to a logarithmic factor, on the minimax separation rate. This optimal rate serves as a benchmark for the difficulty of the testing problem, factoring in model characteristics such as the number "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.06749","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2406.06749/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":"2026-07-05T08:29:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pi0V0R/kcF0IBKA+jLPoJvAiCwTCx63XpvLJq3iesCWZYkDCF72d1tr51AubXcMq8znRgkxblA8EyNluA0gtCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T02:18:38.957946Z"},"content_sha256":"9888a5cf7e47178334fc91ec3516fd196f43156ed3f4b71d2e2ea40af645f5ac","schema_version":"1.0","event_id":"sha256:9888a5cf7e47178334fc91ec3516fd196f43156ed3f4b71d2e2ea40af645f5ac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SB6EOUGV7FTNT6ZHC66LXVTIQD/bundle.json","state_url":"https://pith.science/pith/SB6EOUGV7FTNT6ZHC66LXVTIQD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SB6EOUGV7FTNT6ZHC66LXVTIQD/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":"2026-08-09T02:18:38Z","links":{"resolver":"https://pith.science/pith/SB6EOUGV7FTNT6ZHC66LXVTIQD","bundle":"https://pith.science/pith/SB6EOUGV7FTNT6ZHC66LXVTIQD/bundle.json","state":"https://pith.science/pith/SB6EOUGV7FTNT6ZHC66LXVTIQD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SB6EOUGV7FTNT6ZHC66LXVTIQD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SB6EOUGV7FTNT6ZHC66LXVTIQD","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":"0b4398fbd8bbec54a8f71751f755064f30478767847101e720d1a3d3c324459a","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-06-10T19:25:19Z","title_canon_sha256":"573a7b8f5345226b8f1b0a4aa2e9ed44ddfa7e081a3c31a71a6621cc7ac442a7"},"schema_version":"1.0","source":{"id":"2406.06749","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.06749","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"arxiv_version","alias_value":"2406.06749v1","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.06749","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"pith_short_12","alias_value":"SB6EOUGV7FTN","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"pith_short_16","alias_value":"SB6EOUGV7FTNT6ZH","created_at":"2026-07-05T08:29:49Z"},{"alias_kind":"pith_short_8","alias_value":"SB6EOUGV","created_at":"2026-07-05T08:29:49Z"}],"graph_snapshots":[{"event_id":"sha256:9888a5cf7e47178334fc91ec3516fd196f43156ed3f4b71d2e2ea40af645f5ac","target":"graph","created_at":"2026-07-05T08:29:49Z","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/2406.06749/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning has attracted significant recent attention due to its applicability across a wide range of settings where data is collected and analyzed across disparate locations. In this paper, we study federated nonparametric goodness-of-fit testing in the white-noise-with-drift model under distributed differential privacy (DP) constraints.\n  We first establish matching lower and upper bounds, up to a logarithmic factor, on the minimax separation rate. This optimal rate serves as a benchmark for the difficulty of the testing problem, factoring in model characteristics such as the number ","authors_text":"Abhinav Chakraborty, Lasse Vuursteen, T. Tony Cai","cross_cats":["cs.LG","stat.ML","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-06-10T19:25:19Z","title":"Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.06749","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":"sha256:58048220e337c21b39d5e1a682ca10ba1bdc10608d7e7d3372872d912ab5dcce","target":"record","created_at":"2026-07-05T08:29:49Z","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":"0b4398fbd8bbec54a8f71751f755064f30478767847101e720d1a3d3c324459a","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-06-10T19:25:19Z","title_canon_sha256":"573a7b8f5345226b8f1b0a4aa2e9ed44ddfa7e081a3c31a71a6621cc7ac442a7"},"schema_version":"1.0","source":{"id":"2406.06749","kind":"arxiv","version":1}},"canonical_sha256":"907c4750d5f966d9fb2717bcbbd66880d4c2b8240f90370bbe589faa58824d8c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"907c4750d5f966d9fb2717bcbbd66880d4c2b8240f90370bbe589faa58824d8c","first_computed_at":"2026-07-05T08:29:49.582820Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:29:49.582820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Pt1Hkj5fcpdDgpvuC2GdxiKbZ4dZBEx02Ub/4rULlYQv3JAAY3pVE0K57iCoIxvYv9/89H5kIxz14X3eXk/mBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:29:49.583203Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.06749","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:58048220e337c21b39d5e1a682ca10ba1bdc10608d7e7d3372872d912ab5dcce","sha256:9888a5cf7e47178334fc91ec3516fd196f43156ed3f4b71d2e2ea40af645f5ac"],"state_sha256":"09ee4fe86c93411451426d8059053a450297dcd518c7b2e0722f77cdb5817a58"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EX+66eFEoGVGgMl6W5vc9ZNAxbelLkR5bxzi56UZ34miNDgS1Fi8xJ9PWMUVdsEz10LMo3dWyCsgTzxbhMK8AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T02:18:38.962954Z","bundle_sha256":"44fe260749fdcc82ce36f54f087954c263b4a330eb8ac6d050c9e17535aa3ee0"}}