{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:KAYOKKOHUJROQTZHHM5IX7UVRF","short_pith_number":"pith:KAYOKKOH","canonical_record":{"source":{"id":"2203.04274","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T18:48:55Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"376482a2a4527ec0a81d35492ca3e2ac10e32b46bf4859a22338effbae845aff","abstract_canon_sha256":"3ab28544a165457f0570be0f18cebfb9e4ffb5f80fd1f1a2e1e828dc26cd390f"},"schema_version":"1.0"},"canonical_sha256":"5030e529c7a262e84f273b3a8bfe95896ea97f54bb7a0db2b958b742c70aad4f","source":{"kind":"arxiv","id":"2203.04274","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04274","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04274v1","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04274","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"pith_short_12","alias_value":"KAYOKKOHUJRO","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"pith_short_16","alias_value":"KAYOKKOHUJROQTZH","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"pith_short_8","alias_value":"KAYOKKOH","created_at":"2026-07-05T04:03:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:KAYOKKOHUJROQTZHHM5IX7UVRF","target":"record","payload":{"canonical_record":{"source":{"id":"2203.04274","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T18:48:55Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"376482a2a4527ec0a81d35492ca3e2ac10e32b46bf4859a22338effbae845aff","abstract_canon_sha256":"3ab28544a165457f0570be0f18cebfb9e4ffb5f80fd1f1a2e1e828dc26cd390f"},"schema_version":"1.0"},"canonical_sha256":"5030e529c7a262e84f273b3a8bfe95896ea97f54bb7a0db2b958b742c70aad4f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:03:07.734876Z","signature_b64":"V68XqCOR6uBh7bWZjE1ZcDXPPZY4CeOBJSEW+hSBbme3Jgf06aO1NFf5Yh02NKDBB7isetwTUIghlzw7FcS3DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5030e529c7a262e84f273b3a8bfe95896ea97f54bb7a0db2b958b742c70aad4f","last_reissued_at":"2026-07-05T04:03:07.734489Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:03:07.734489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.04274","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":"2026-07-05T04:03:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/KvFPmymilZT0m8/BkzwKRqMpU3ovkU5TLs5UtF0QocxGmiqrw3MI+4jSebaNcf8yisT/AM0FzFBZAUk0UYuCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:41:26.054574Z"},"content_sha256":"a23e7d405602ac1964524355873ce40c06fc44333570b85941ab072069628fcc","schema_version":"1.0","event_id":"sha256:a23e7d405602ac1964524355873ce40c06fc44333570b85941ab072069628fcc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:KAYOKKOHUJROQTZHHM5IX7UVRF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Leveraging Initial Hints for Free in Stochastic Linear Bandits","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.LG","authors_text":"Abhimanyu Das, Ashok Cutkosky, Chris Dann, Qiuyi (Richard) Zhang","submitted_at":"2022-03-08T18:48:55Z","abstract_excerpt":"We study the setting of optimizing with bandit feedback with additional prior knowledge provided to the learner in the form of an initial hint of the optimal action. We present a novel algorithm for stochastic linear bandits that uses this hint to improve its regret to $\\tilde O(\\sqrt{T})$ when the hint is accurate, while maintaining a minimax-optimal $\\tilde O(d\\sqrt{T})$ regret independent of the quality of the hint. Furthermore, we provide a Pareto frontier of tight tradeoffs between best-case and worst-case regret, with matching lower bounds. Perhaps surprisingly, our work shows that lever"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04274","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/2203.04274/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":"2026-07-05T04:03:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VF12+s3Abs6GGa3s0eARyLHqJAhYDQ4GRR/0ABl1vmg2QDqwnAgh/TjKmg09Dx4R1aHVLAniSVbK6wUVe3/tBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:41:26.055647Z"},"content_sha256":"dc40d0d583dd08bc4044f432e4569ba02f6a3d3376535d74882a7bc739c91577","schema_version":"1.0","event_id":"sha256:dc40d0d583dd08bc4044f432e4569ba02f6a3d3376535d74882a7bc739c91577"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KAYOKKOHUJROQTZHHM5IX7UVRF/bundle.json","state_url":"https://pith.science/pith/KAYOKKOHUJROQTZHHM5IX7UVRF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KAYOKKOHUJROQTZHHM5IX7UVRF/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":"2026-08-05T15:41:26Z","links":{"resolver":"https://pith.science/pith/KAYOKKOHUJROQTZHHM5IX7UVRF","bundle":"https://pith.science/pith/KAYOKKOHUJROQTZHHM5IX7UVRF/bundle.json","state":"https://pith.science/pith/KAYOKKOHUJROQTZHHM5IX7UVRF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KAYOKKOHUJROQTZHHM5IX7UVRF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KAYOKKOHUJROQTZHHM5IX7UVRF","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":"3ab28544a165457f0570be0f18cebfb9e4ffb5f80fd1f1a2e1e828dc26cd390f","cross_cats_sorted":["cs.DS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T18:48:55Z","title_canon_sha256":"376482a2a4527ec0a81d35492ca3e2ac10e32b46bf4859a22338effbae845aff"},"schema_version":"1.0","source":{"id":"2203.04274","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04274","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04274v1","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04274","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"pith_short_12","alias_value":"KAYOKKOHUJRO","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"pith_short_16","alias_value":"KAYOKKOHUJROQTZH","created_at":"2026-07-05T04:03:07Z"},{"alias_kind":"pith_short_8","alias_value":"KAYOKKOH","created_at":"2026-07-05T04:03:07Z"}],"graph_snapshots":[{"event_id":"sha256:dc40d0d583dd08bc4044f432e4569ba02f6a3d3376535d74882a7bc739c91577","target":"graph","created_at":"2026-07-05T04:03:07Z","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/2203.04274/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study the setting of optimizing with bandit feedback with additional prior knowledge provided to the learner in the form of an initial hint of the optimal action. We present a novel algorithm for stochastic linear bandits that uses this hint to improve its regret to $\\tilde O(\\sqrt{T})$ when the hint is accurate, while maintaining a minimax-optimal $\\tilde O(d\\sqrt{T})$ regret independent of the quality of the hint. Furthermore, we provide a Pareto frontier of tight tradeoffs between best-case and worst-case regret, with matching lower bounds. Perhaps surprisingly, our work shows that lever","authors_text":"Abhimanyu Das, Ashok Cutkosky, Chris Dann, Qiuyi (Richard) Zhang","cross_cats":["cs.DS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T18:48:55Z","title":"Leveraging Initial Hints for Free in Stochastic Linear Bandits"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04274","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:a23e7d405602ac1964524355873ce40c06fc44333570b85941ab072069628fcc","target":"record","created_at":"2026-07-05T04:03:07Z","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":"3ab28544a165457f0570be0f18cebfb9e4ffb5f80fd1f1a2e1e828dc26cd390f","cross_cats_sorted":["cs.DS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T18:48:55Z","title_canon_sha256":"376482a2a4527ec0a81d35492ca3e2ac10e32b46bf4859a22338effbae845aff"},"schema_version":"1.0","source":{"id":"2203.04274","kind":"arxiv","version":1}},"canonical_sha256":"5030e529c7a262e84f273b3a8bfe95896ea97f54bb7a0db2b958b742c70aad4f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5030e529c7a262e84f273b3a8bfe95896ea97f54bb7a0db2b958b742c70aad4f","first_computed_at":"2026-07-05T04:03:07.734489Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:03:07.734489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V68XqCOR6uBh7bWZjE1ZcDXPPZY4CeOBJSEW+hSBbme3Jgf06aO1NFf5Yh02NKDBB7isetwTUIghlzw7FcS3DA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:03:07.734876Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.04274","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a23e7d405602ac1964524355873ce40c06fc44333570b85941ab072069628fcc","sha256:dc40d0d583dd08bc4044f432e4569ba02f6a3d3376535d74882a7bc739c91577"],"state_sha256":"b76df56a3e3724b419c2082af2daca312b7e903fd6335a6c9638eb0d97211b03"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tc1JLKYNspD31273Jzl+cHdDZVfvI1WVm2SQAhGSgfb0BLldDfjtNUPMfR95uphzr2C/Zdt07TVTAgqZV0iOBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T15:41:26.068176Z","bundle_sha256":"ea1aa06216c956a1660cf0ed1efc854902f2491fad7b7c6c6fc94122ec268b6d"}}