{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:3PQWUS3QDE26PDOGEAMDEAZCZB","short_pith_number":"pith:3PQWUS3Q","canonical_record":{"source":{"id":"2106.04763","kind":"arxiv","version":8},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T01:32:43Z","cross_cats_sorted":[],"title_canon_sha256":"a7c83151fd9d6182d2a0d5bef33a17676ba8fcfadd46e536a1b07f04b63f6947","abstract_canon_sha256":"7de29a5a038b8f163c4d9f80af553bc6b0dd1817a6973d90dc47371d636025df"},"schema_version":"1.0"},"canonical_sha256":"dbe16a4b701935e78dc62018320322c85df19057c1e5185f6fac21255d483105","source":{"kind":"arxiv","id":"2106.04763","version":8},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.04763","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"arxiv_version","alias_value":"2106.04763v8","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04763","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"pith_short_12","alias_value":"3PQWUS3QDE26","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"pith_short_16","alias_value":"3PQWUS3QDE26PDOG","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"pith_short_8","alias_value":"3PQWUS3Q","created_at":"2026-07-05T06:27:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:3PQWUS3QDE26PDOGEAMDEAZCZB","target":"record","payload":{"canonical_record":{"source":{"id":"2106.04763","kind":"arxiv","version":8},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T01:32:43Z","cross_cats_sorted":[],"title_canon_sha256":"a7c83151fd9d6182d2a0d5bef33a17676ba8fcfadd46e536a1b07f04b63f6947","abstract_canon_sha256":"7de29a5a038b8f163c4d9f80af553bc6b0dd1817a6973d90dc47371d636025df"},"schema_version":"1.0"},"canonical_sha256":"dbe16a4b701935e78dc62018320322c85df19057c1e5185f6fac21255d483105","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:27:37.217259Z","signature_b64":"PU+e4es9nJBNnyPqSOoCnC1FtYOpBG+PIiE3zhBcHxCpH76zyP6loGh0IuIMFSQPm3k3q+DLIOuwBH+fezr8Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dbe16a4b701935e78dc62018320322c85df19057c1e5185f6fac21255d483105","last_reissued_at":"2026-07-05T06:27:37.216889Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:27:37.216889Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.04763","source_version":8,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:27:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qEBHhMHuJrGTX+Ut3DPmJSdbiZ21PCVQU02kHG1Z91MbjZkrDTZ8HnYdfNqdqvQggfuyd2cxNhg0m5q+CtbTAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:09:15.373721Z"},"content_sha256":"2a2e2d8bb8f628960f016129b44c96365a3e9121783c2d3a531f111945eb5192","schema_version":"1.0","event_id":"sha256:2a2e2d8bb8f628960f016129b44c96365a3e9121783c2d3a531f111945eb5192"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:3PQWUS3QDE26PDOGEAMDEAZCZB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fixed-Budget Best-Arm Identification in Structured Bandits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Branislav Kveton, Mohammad Ghavamzadeh, Mohammad Javad Azizi","submitted_at":"2021-06-09T01:32:43Z","abstract_excerpt":"Best-arm identification (BAI) in a fixed-budget setting is a bandit problem where the learning agent maximizes the probability of identifying the optimal (best) arm after a fixed number of observations. Most works on this topic study unstructured problems with a small number of arms, which limits their applicability. We propose a general tractable algorithm that incorporates the structure, by successively eliminating suboptimal arms based on their mean reward estimates from a joint generalization model. We analyze our algorithm in linear and generalized linear models (GLMs), and propose a prac"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04763","kind":"arxiv","version":8},"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/2106.04763/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":"2026-07-05T06:27:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZAc/es5BjfDRfr3/a8PTVcUGP/DLUlzFBLm1ZgJDsKel+BvFYAW6mE18jhJZrW8UOs8P5tZ+RN+NXJFRN++HDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:09:15.374243Z"},"content_sha256":"307caf6d098015356850c56eb93b28805d60a11e28d44bb5a014e9f0ff427890","schema_version":"1.0","event_id":"sha256:307caf6d098015356850c56eb93b28805d60a11e28d44bb5a014e9f0ff427890"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3PQWUS3QDE26PDOGEAMDEAZCZB/bundle.json","state_url":"https://pith.science/pith/3PQWUS3QDE26PDOGEAMDEAZCZB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3PQWUS3QDE26PDOGEAMDEAZCZB/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":"2026-08-08T04:09:15Z","links":{"resolver":"https://pith.science/pith/3PQWUS3QDE26PDOGEAMDEAZCZB","bundle":"https://pith.science/pith/3PQWUS3QDE26PDOGEAMDEAZCZB/bundle.json","state":"https://pith.science/pith/3PQWUS3QDE26PDOGEAMDEAZCZB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3PQWUS3QDE26PDOGEAMDEAZCZB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:3PQWUS3QDE26PDOGEAMDEAZCZB","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":"7de29a5a038b8f163c4d9f80af553bc6b0dd1817a6973d90dc47371d636025df","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T01:32:43Z","title_canon_sha256":"a7c83151fd9d6182d2a0d5bef33a17676ba8fcfadd46e536a1b07f04b63f6947"},"schema_version":"1.0","source":{"id":"2106.04763","kind":"arxiv","version":8}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.04763","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"arxiv_version","alias_value":"2106.04763v8","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04763","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"pith_short_12","alias_value":"3PQWUS3QDE26","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"pith_short_16","alias_value":"3PQWUS3QDE26PDOG","created_at":"2026-07-05T06:27:37Z"},{"alias_kind":"pith_short_8","alias_value":"3PQWUS3Q","created_at":"2026-07-05T06:27:37Z"}],"graph_snapshots":[{"event_id":"sha256:307caf6d098015356850c56eb93b28805d60a11e28d44bb5a014e9f0ff427890","target":"graph","created_at":"2026-07-05T06:27:37Z","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/2106.04763/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Best-arm identification (BAI) in a fixed-budget setting is a bandit problem where the learning agent maximizes the probability of identifying the optimal (best) arm after a fixed number of observations. Most works on this topic study unstructured problems with a small number of arms, which limits their applicability. We propose a general tractable algorithm that incorporates the structure, by successively eliminating suboptimal arms based on their mean reward estimates from a joint generalization model. We analyze our algorithm in linear and generalized linear models (GLMs), and propose a prac","authors_text":"Branislav Kveton, Mohammad Ghavamzadeh, Mohammad Javad Azizi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T01:32:43Z","title":"Fixed-Budget Best-Arm Identification in Structured Bandits"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04763","kind":"arxiv","version":8},"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":"sha256:2a2e2d8bb8f628960f016129b44c96365a3e9121783c2d3a531f111945eb5192","target":"record","created_at":"2026-07-05T06:27:37Z","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":"7de29a5a038b8f163c4d9f80af553bc6b0dd1817a6973d90dc47371d636025df","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T01:32:43Z","title_canon_sha256":"a7c83151fd9d6182d2a0d5bef33a17676ba8fcfadd46e536a1b07f04b63f6947"},"schema_version":"1.0","source":{"id":"2106.04763","kind":"arxiv","version":8}},"canonical_sha256":"dbe16a4b701935e78dc62018320322c85df19057c1e5185f6fac21255d483105","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dbe16a4b701935e78dc62018320322c85df19057c1e5185f6fac21255d483105","first_computed_at":"2026-07-05T06:27:37.216889Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:27:37.216889Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PU+e4es9nJBNnyPqSOoCnC1FtYOpBG+PIiE3zhBcHxCpH76zyP6loGh0IuIMFSQPm3k3q+DLIOuwBH+fezr8Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T06:27:37.217259Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.04763","source_kind":"arxiv","source_version":8}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2a2e2d8bb8f628960f016129b44c96365a3e9121783c2d3a531f111945eb5192","sha256:307caf6d098015356850c56eb93b28805d60a11e28d44bb5a014e9f0ff427890"],"state_sha256":"f7c2b81f6af9f054bd6e9a0132a051957d0f6072beaaea0f8c86db3529b4e9ee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"64JAdsQ9GaJiCGJqGed0jzmPzimN9dhrRO3/dB8zaBBC2ES9jxujdC0MLquMUI2Y/AJ2Ont9NTlS8gqfvvMsCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T04:09:15.379229Z","bundle_sha256":"e8c3f38790715ddc752f7a7d7de7dd69be84be5091118d8e283f6fd2e6a9bfe0"}}