{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:LVE7FSXRM3RJUGJ5X5CG5Y3YL7","short_pith_number":"pith:LVE7FSXR","schema_version":"1.0","canonical_sha256":"5d49f2caf166e29a193dbf446ee3785fd86f3a85a1253d78291c51afa5f4c4e2","source":{"kind":"arxiv","id":"2502.00871","version":1},"attestation_state":"computed","paper":{"title":"Modified Adaptive Tree-Structured Parzen Estimator for Hyperparameter Optimization","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Jacek Ma\\'ndziuk, Szymon Sieradzki","submitted_at":"2025-02-02T18:45:28Z","abstract_excerpt":"In this paper, we review hyperparameter optimization methods for machine learning models, with a particular focus on the Adaptive Tree-Structured Parzen Estimator (ATPE) algorithm. We propose several modifications to ATPE and assess their efficacy on a diverse set of standard benchmark functions. Experimental results demonstrate that the proposed modifications significantly improve the effectiveness of ATPE hyperparameter optimization on selected benchmarks, a finding that holds practical relevance for their application in real-world machine learning / optimization tasks."},"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":"2502.00871","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-02T18:45:28Z","cross_cats_sorted":[],"title_canon_sha256":"e61e8fdf1f23ff95233bb57987af976a4eede2fb7c25bf35c793a6578176870b","abstract_canon_sha256":"b018efd99bff16b8c6dab36f13a867a2646d2f77dbd1701c38921ff5b12b7194"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:08:39.415618Z","signature_b64":"mNkoLXFeKX7KcVlTIZwtrhOmQy364LkLtwwpyxT49P40PasNsqAhM7841IjQjrfX/bfmk3Shu0jwnDKZR4+4Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d49f2caf166e29a193dbf446ee3785fd86f3a85a1253d78291c51afa5f4c4e2","last_reissued_at":"2026-07-05T10:08:39.415232Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:08:39.415232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Modified Adaptive Tree-Structured Parzen Estimator for Hyperparameter Optimization","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Jacek Ma\\'ndziuk, Szymon Sieradzki","submitted_at":"2025-02-02T18:45:28Z","abstract_excerpt":"In this paper, we review hyperparameter optimization methods for machine learning models, with a particular focus on the Adaptive Tree-Structured Parzen Estimator (ATPE) algorithm. We propose several modifications to ATPE and assess their efficacy on a diverse set of standard benchmark functions. Experimental results demonstrate that the proposed modifications significantly improve the effectiveness of ATPE hyperparameter optimization on selected benchmarks, a finding that holds practical relevance for their application in real-world machine learning / optimization tasks."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.00871","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/2502.00871/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2502.00871","created_at":"2026-07-05T10:08:39.415289+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.00871v1","created_at":"2026-07-05T10:08:39.415289+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.00871","created_at":"2026-07-05T10:08:39.415289+00:00"},{"alias_kind":"pith_short_12","alias_value":"LVE7FSXRM3RJ","created_at":"2026-07-05T10:08:39.415289+00:00"},{"alias_kind":"pith_short_16","alias_value":"LVE7FSXRM3RJUGJ5","created_at":"2026-07-05T10:08:39.415289+00:00"},{"alias_kind":"pith_short_8","alias_value":"LVE7FSXR","created_at":"2026-07-05T10:08:39.415289+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/LVE7FSXRM3RJUGJ5X5CG5Y3YL7","json":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7.json","graph_json":"https://pith.science/api/pith-number/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/graph.json","events_json":"https://pith.science/api/pith-number/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/events.json","paper":"https://pith.science/paper/LVE7FSXR"},"agent_actions":{"view_html":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7","download_json":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7.json","view_paper":"https://pith.science/paper/LVE7FSXR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.00871&json=true","fetch_graph":"https://pith.science/api/pith-number/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/graph.json","fetch_events":"https://pith.science/api/pith-number/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/action/storage_attestation","attest_author":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/action/author_attestation","sign_citation":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/action/citation_signature","submit_replication":"https://pith.science/pith/LVE7FSXRM3RJUGJ5X5CG5Y3YL7/action/replication_record"}},"created_at":"2026-07-05T10:08:39.415289+00:00","updated_at":"2026-07-05T10:08:39.415289+00:00"}