{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:SXEWKWTE4ZV3BVM6N6JYUWIMSB","short_pith_number":"pith:SXEWKWTE","canonical_record":{"source":{"id":"2211.08572","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-15T23:29:51Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"37737039790cafc101a89e78d0403ccf630e064693862aecdccea7d5b99cc1ed","abstract_canon_sha256":"29761f00f7c83380954811fcf287467c179e6235b883b1e1c34a6536af48ba57"},"schema_version":"1.0"},"canonical_sha256":"95c9655a64e66bb0d59e6f938a590c907a353e6b8d7980ac5b4f0ab106138b6c","source":{"kind":"arxiv","id":"2211.08572","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.08572","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"arxiv_version","alias_value":"2211.08572v3","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.08572","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"pith_short_12","alias_value":"SXEWKWTE4ZV3","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"pith_short_16","alias_value":"SXEWKWTE4ZV3BVM6","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"pith_short_8","alias_value":"SXEWKWTE","created_at":"2026-07-05T06:21:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:SXEWKWTE4ZV3BVM6N6JYUWIMSB","target":"record","payload":{"canonical_record":{"source":{"id":"2211.08572","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-15T23:29:51Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"37737039790cafc101a89e78d0403ccf630e064693862aecdccea7d5b99cc1ed","abstract_canon_sha256":"29761f00f7c83380954811fcf287467c179e6235b883b1e1c34a6536af48ba57"},"schema_version":"1.0"},"canonical_sha256":"95c9655a64e66bb0d59e6f938a590c907a353e6b8d7980ac5b4f0ab106138b6c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:21:04.441831Z","signature_b64":"8oDDIr4I+VtZTvpZUqy0q6t/TXLafmWmMX1PTU77c8liDP2avRXGLKUNh58bVogQB8qcvhIOx5gnBEN24/KhAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95c9655a64e66bb0d59e6f938a590c907a353e6b8d7980ac5b4f0ab106138b6c","last_reissued_at":"2026-07-05T06:21:04.441351Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:21:04.441351Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.08572","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:21:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OM5SyMF8DDEfRtVt54ukOvp4I1MwxImcBjDEAkrW8onA/uwbvthDhvVj+i4R6dEtLzbiji8U16QRTY5CShkGAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T22:01:48.594776Z"},"content_sha256":"4518b1d12ab6975c94385d8736b5921491bb5338c67b6aba8e9ec5ebfdd9fe8e","schema_version":"1.0","event_id":"sha256:4518b1d12ab6975c94385d8736b5921491bb5338c67b6aba8e9ec5ebfdd9fe8e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:SXEWKWTE4ZV3BVM6N6JYUWIMSB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Fixed-Budget Best-Arm Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alexia Atsidakou, Branislav Kveton, Sujay Sanghavi, Sumeet Katariya","submitted_at":"2022-11-15T23:29:51Z","abstract_excerpt":"Fixed-budget best-arm identification (BAI) is a bandit problem where the agent maximizes the probability of identifying the optimal arm within a fixed budget of observations. In this work, we study this problem in the Bayesian setting. We propose a Bayesian elimination algorithm and derive an upper bound on its probability of misidentifying the optimal arm. The bound reflects the quality of the prior and is the first distribution-dependent bound in this setting. We prove it using a frequentist-like argument, where we carry the prior through, and then integrate out the bandit instance at the en"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.08572","kind":"arxiv","version":3},"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/2211.08572/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":"2026-07-05T06:21:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9qI/5GidP9Pmo2CVmVw2H7zHCSpNN7g+8wAMuhb7SAapc2i9iIwq6L0mVkDkL9/c/0aB5bMIYLSP50Z/gieABg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T22:01:48.595292Z"},"content_sha256":"73d030b792543e3e2ac7f7e6b556169446e22d9d7c224e3f0c659925bded9fe5","schema_version":"1.0","event_id":"sha256:73d030b792543e3e2ac7f7e6b556169446e22d9d7c224e3f0c659925bded9fe5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SXEWKWTE4ZV3BVM6N6JYUWIMSB/bundle.json","state_url":"https://pith.science/pith/SXEWKWTE4ZV3BVM6N6JYUWIMSB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SXEWKWTE4ZV3BVM6N6JYUWIMSB/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":"2026-08-19T22:01:48Z","links":{"resolver":"https://pith.science/pith/SXEWKWTE4ZV3BVM6N6JYUWIMSB","bundle":"https://pith.science/pith/SXEWKWTE4ZV3BVM6N6JYUWIMSB/bundle.json","state":"https://pith.science/pith/SXEWKWTE4ZV3BVM6N6JYUWIMSB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SXEWKWTE4ZV3BVM6N6JYUWIMSB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:SXEWKWTE4ZV3BVM6N6JYUWIMSB","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":"29761f00f7c83380954811fcf287467c179e6235b883b1e1c34a6536af48ba57","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-15T23:29:51Z","title_canon_sha256":"37737039790cafc101a89e78d0403ccf630e064693862aecdccea7d5b99cc1ed"},"schema_version":"1.0","source":{"id":"2211.08572","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.08572","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"arxiv_version","alias_value":"2211.08572v3","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.08572","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"pith_short_12","alias_value":"SXEWKWTE4ZV3","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"pith_short_16","alias_value":"SXEWKWTE4ZV3BVM6","created_at":"2026-07-05T06:21:04Z"},{"alias_kind":"pith_short_8","alias_value":"SXEWKWTE","created_at":"2026-07-05T06:21:04Z"}],"graph_snapshots":[{"event_id":"sha256:73d030b792543e3e2ac7f7e6b556169446e22d9d7c224e3f0c659925bded9fe5","target":"graph","created_at":"2026-07-05T06:21:04Z","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/2211.08572/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fixed-budget best-arm identification (BAI) is a bandit problem where the agent maximizes the probability of identifying the optimal arm within a fixed budget of observations. In this work, we study this problem in the Bayesian setting. We propose a Bayesian elimination algorithm and derive an upper bound on its probability of misidentifying the optimal arm. The bound reflects the quality of the prior and is the first distribution-dependent bound in this setting. We prove it using a frequentist-like argument, where we carry the prior through, and then integrate out the bandit instance at the en","authors_text":"Alexia Atsidakou, Branislav Kveton, Sujay Sanghavi, Sumeet Katariya","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-15T23:29:51Z","title":"Bayesian Fixed-Budget Best-Arm Identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.08572","kind":"arxiv","version":3},"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":"sha256:4518b1d12ab6975c94385d8736b5921491bb5338c67b6aba8e9ec5ebfdd9fe8e","target":"record","created_at":"2026-07-05T06:21:04Z","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":"29761f00f7c83380954811fcf287467c179e6235b883b1e1c34a6536af48ba57","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-15T23:29:51Z","title_canon_sha256":"37737039790cafc101a89e78d0403ccf630e064693862aecdccea7d5b99cc1ed"},"schema_version":"1.0","source":{"id":"2211.08572","kind":"arxiv","version":3}},"canonical_sha256":"95c9655a64e66bb0d59e6f938a590c907a353e6b8d7980ac5b4f0ab106138b6c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95c9655a64e66bb0d59e6f938a590c907a353e6b8d7980ac5b4f0ab106138b6c","first_computed_at":"2026-07-05T06:21:04.441351Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:21:04.441351Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8oDDIr4I+VtZTvpZUqy0q6t/TXLafmWmMX1PTU77c8liDP2avRXGLKUNh58bVogQB8qcvhIOx5gnBEN24/KhAg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:21:04.441831Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.08572","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4518b1d12ab6975c94385d8736b5921491bb5338c67b6aba8e9ec5ebfdd9fe8e","sha256:73d030b792543e3e2ac7f7e6b556169446e22d9d7c224e3f0c659925bded9fe5"],"state_sha256":"86a97021b63648c1d5dff76f8b17567271f0a57e72bfd64ac38ebeae0b5b1da4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MkxxPeQCf0nEBPVSEjuEsZuj47rYhNBjNWSB5SMotAgtZLwh7+aUh3qYd8g9y+UDaRQ98RXja6jvn+9cCK0wCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T22:01:48.600406Z","bundle_sha256":"e54bf1c590079587be63219fa80907a129ba399b7cbcd9f31db39ad5b86517f7"}}