{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:P7SNESKLLD6UDI4MGULYNKWOSY","short_pith_number":"pith:P7SNESKL","schema_version":"1.0","canonical_sha256":"7fe4d2494b58fd41a38c351786aace962966d8805e456a11cfd3a16349a8190e","source":{"kind":"arxiv","id":"1603.02752","version":2},"attestation_state":"computed","paper":{"title":"Best-of-K Bandits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Benjamin Recht, Kevin Jamieson, Max Simchowitz","submitted_at":"2016-03-09T00:55:58Z","abstract_excerpt":"This paper studies the Best-of-K Bandit game: At each time the player chooses a subset S among all N-choose-K possible options and observes reward max(X(i) : i in S) where X is a random vector drawn from a joint distribution. The objective is to identify the subset that achieves the highest expected reward with high probability using as few queries as possible. We present distribution-dependent lower bounds based on a particular construction which force a learner to consider all N-choose-K subsets, and match naive extensions of known upper bounds in the bandit setting obtained by treating each"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1603.02752","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-03-09T00:55:58Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"9df19c7cf5927a828aa1404b1ed0548fb1767f687dfbe46bd5f92e954b26870f","abstract_canon_sha256":"c8b22cca0e3fc57642947250f0b144f697df1762e384e9a68c978dea28e45b51"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:18:52.147959Z","signature_b64":"Q3IdIgpQCOl1GsUOhEnqgKHNOQwbdNJXzeuPGDrnn3DPjpowtTfRrX16RX9ct6IOwcBdDGC7elKiTaQC8ABNDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7fe4d2494b58fd41a38c351786aace962966d8805e456a11cfd3a16349a8190e","last_reissued_at":"2026-05-18T01:18:52.147481Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:18:52.147481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Best-of-K Bandits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Benjamin Recht, Kevin Jamieson, Max Simchowitz","submitted_at":"2016-03-09T00:55:58Z","abstract_excerpt":"This paper studies the Best-of-K Bandit game: At each time the player chooses a subset S among all N-choose-K possible options and observes reward max(X(i) : i in S) where X is a random vector drawn from a joint distribution. The objective is to identify the subset that achieves the highest expected reward with high probability using as few queries as possible. We present distribution-dependent lower bounds based on a particular construction which force a learner to consider all N-choose-K subsets, and match naive extensions of known upper bounds in the bandit setting obtained by treating each"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.02752","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1603.02752","created_at":"2026-05-18T01:18:52.147553+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.02752v2","created_at":"2026-05-18T01:18:52.147553+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.02752","created_at":"2026-05-18T01:18:52.147553+00:00"},{"alias_kind":"pith_short_12","alias_value":"P7SNESKLLD6U","created_at":"2026-05-18T12:30:39.010887+00:00"},{"alias_kind":"pith_short_16","alias_value":"P7SNESKLLD6UDI4M","created_at":"2026-05-18T12:30:39.010887+00:00"},{"alias_kind":"pith_short_8","alias_value":"P7SNESKL","created_at":"2026-05-18T12:30:39.010887+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY","json":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY.json","graph_json":"https://pith.science/api/pith-number/P7SNESKLLD6UDI4MGULYNKWOSY/graph.json","events_json":"https://pith.science/api/pith-number/P7SNESKLLD6UDI4MGULYNKWOSY/events.json","paper":"https://pith.science/paper/P7SNESKL"},"agent_actions":{"view_html":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY","download_json":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY.json","view_paper":"https://pith.science/paper/P7SNESKL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.02752&json=true","fetch_graph":"https://pith.science/api/pith-number/P7SNESKLLD6UDI4MGULYNKWOSY/graph.json","fetch_events":"https://pith.science/api/pith-number/P7SNESKLLD6UDI4MGULYNKWOSY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY/action/storage_attestation","attest_author":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY/action/author_attestation","sign_citation":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY/action/citation_signature","submit_replication":"https://pith.science/pith/P7SNESKLLD6UDI4MGULYNKWOSY/action/replication_record"}},"created_at":"2026-05-18T01:18:52.147553+00:00","updated_at":"2026-05-18T01:18:52.147553+00:00"}