{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:QDCJZQUDIGWOZBGAW3YWKGHXT5","short_pith_number":"pith:QDCJZQUD","schema_version":"1.0","canonical_sha256":"80c49cc28341acec84c0b6f16518f79f6dcea13cdfce20e3484e79f89e773860","source":{"kind":"arxiv","id":"1807.01279","version":1},"attestation_state":"computed","paper":{"title":"Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"stat.ML","authors_text":"Dipti Jasrasaria, Edward O. Pyzer-Knapp","submitted_at":"2018-07-03T16:56:05Z","abstract_excerpt":"Bayesian optimization offers the possibility of optimizing black-box operations not accessible through traditional techniques. The success of Bayesian optimization methods such as Expected Improvement (EI) are significantly affected by the degree of trade-off between exploration and exploitation. Too much exploration can lead to inefficient optimization protocols, whilst too much exploitation leaves the protocol open to strong initial biases, and a high chance of getting stuck in a local minimum. Typically, a constant margin is used to control this trade-off, which results in yet another hyper"},"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":"1807.01279","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-03T16:56:05Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"7693d140b82e0bbf86a4156afc96bf34aeffbf045c56f01ba37379b845e2abf2","abstract_canon_sha256":"3196ed7d1f2f59bbdde1f9eba67e427e6b1dffb9855cc08a89d3791c0a06548a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:11:44.730423Z","signature_b64":"FjBalKeXSFebDUlBq7u8tbVgfvao8Ln4wbm4j2+pXlnD8UcUxii8xOrc7DJkzTXjzFYQFZGS7XvLL3NZiKPYDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"80c49cc28341acec84c0b6f16518f79f6dcea13cdfce20e3484e79f89e773860","last_reissued_at":"2026-05-18T00:11:44.729797Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:11:44.729797Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"stat.ML","authors_text":"Dipti Jasrasaria, Edward O. Pyzer-Knapp","submitted_at":"2018-07-03T16:56:05Z","abstract_excerpt":"Bayesian optimization offers the possibility of optimizing black-box operations not accessible through traditional techniques. The success of Bayesian optimization methods such as Expected Improvement (EI) are significantly affected by the degree of trade-off between exploration and exploitation. Too much exploration can lead to inefficient optimization protocols, whilst too much exploitation leaves the protocol open to strong initial biases, and a high chance of getting stuck in a local minimum. Typically, a constant margin is used to control this trade-off, which results in yet another hyper"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.01279","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":""},"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":"1807.01279","created_at":"2026-05-18T00:11:44.729916+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.01279v1","created_at":"2026-05-18T00:11:44.729916+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.01279","created_at":"2026-05-18T00:11:44.729916+00:00"},{"alias_kind":"pith_short_12","alias_value":"QDCJZQUDIGWO","created_at":"2026-05-18T12:32:46.962924+00:00"},{"alias_kind":"pith_short_16","alias_value":"QDCJZQUDIGWOZBGA","created_at":"2026-05-18T12:32:46.962924+00:00"},{"alias_kind":"pith_short_8","alias_value":"QDCJZQUD","created_at":"2026-05-18T12:32:46.962924+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/QDCJZQUDIGWOZBGAW3YWKGHXT5","json":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5.json","graph_json":"https://pith.science/api/pith-number/QDCJZQUDIGWOZBGAW3YWKGHXT5/graph.json","events_json":"https://pith.science/api/pith-number/QDCJZQUDIGWOZBGAW3YWKGHXT5/events.json","paper":"https://pith.science/paper/QDCJZQUD"},"agent_actions":{"view_html":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5","download_json":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5.json","view_paper":"https://pith.science/paper/QDCJZQUD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.01279&json=true","fetch_graph":"https://pith.science/api/pith-number/QDCJZQUDIGWOZBGAW3YWKGHXT5/graph.json","fetch_events":"https://pith.science/api/pith-number/QDCJZQUDIGWOZBGAW3YWKGHXT5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5/action/storage_attestation","attest_author":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5/action/author_attestation","sign_citation":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5/action/citation_signature","submit_replication":"https://pith.science/pith/QDCJZQUDIGWOZBGAW3YWKGHXT5/action/replication_record"}},"created_at":"2026-05-18T00:11:44.729916+00:00","updated_at":"2026-05-18T00:11:44.729916+00:00"}