{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:6YXPVLXIBKABQIIOOGIHJKENZE","short_pith_number":"pith:6YXPVLXI","canonical_record":{"source":{"id":"2012.03826","kind":"arxiv","version":6},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-07T16:21:12Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"f9123af09792727d3c47d92fe4877d0a4d43beef2bb66644c421777c5ff04a41","abstract_canon_sha256":"7085386cea44a1f9f7f5656ddd6a3e5467e08024a3e3d883c7c3808414479628"},"schema_version":"1.0"},"canonical_sha256":"f62efaaee80a8018210e719074a88dc93783d626b70eec631e1e3072676dfd28","source":{"kind":"arxiv","id":"2012.03826","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.03826","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"arxiv_version","alias_value":"2012.03826v6","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.03826","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"pith_short_12","alias_value":"6YXPVLXIBKAB","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"pith_short_16","alias_value":"6YXPVLXIBKABQIIO","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"pith_short_8","alias_value":"6YXPVLXI","created_at":"2026-07-05T04:26:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:6YXPVLXIBKABQIIOOGIHJKENZE","target":"record","payload":{"canonical_record":{"source":{"id":"2012.03826","kind":"arxiv","version":6},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-07T16:21:12Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"f9123af09792727d3c47d92fe4877d0a4d43beef2bb66644c421777c5ff04a41","abstract_canon_sha256":"7085386cea44a1f9f7f5656ddd6a3e5467e08024a3e3d883c7c3808414479628"},"schema_version":"1.0"},"canonical_sha256":"f62efaaee80a8018210e719074a88dc93783d626b70eec631e1e3072676dfd28","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:26:18.595999Z","signature_b64":"FcS0TBVZoMMWASrwxwS+kRlGKEutZYbjBwkMPXym4nZskpFabtGYCwXMn0IEa2xoOJdmfmqlTgAkgSdYr8HQAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f62efaaee80a8018210e719074a88dc93783d626b70eec631e1e3072676dfd28","last_reissued_at":"2026-07-05T04:26:18.595489Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:26:18.595489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2012.03826","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:26:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gGa+rdn1Tl6FO55Cw0quF8mGUapwy6iZy5vdBrpK5QpMFUL1TZjulhPUVIV9r/c+1QGSCiEHVeAOf3JgBwP1CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T07:56:23.955097Z"},"content_sha256":"b86acbc66661deb0a82ee922316167434fa4ef1ff7268bc435ae689fd6e53260","schema_version":"1.0","event_id":"sha256:b86acbc66661deb0a82ee922316167434fa4ef1ff7268bc435ae689fd6e53260"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:6YXPVLXIBKABQIIOOGIHJKENZE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.LG","authors_text":"Alexander I. Cowen-Rivers, Alexandre Max Maraval, Antoine Grosnit, Haitham Bou Ammar, Hao Jianye, Jan Peters, Jun Wang, Rasul Tutunov, Ryan Rhys Griffiths, Wenlong Lyu, Zhi Wang","submitted_at":"2020-12-07T16:21:12Z","abstract_excerpt":"In this work we rigorously analyse assumptions inherent to black-box optimisation hyper-parameter tuning tasks. Our results on the Bayesmark benchmark indicate that heteroscedasticity and non-stationarity pose significant challenges for black-box optimisers. Based on these findings, we propose a Heteroscedastic and Evolutionary Bayesian Optimisation solver (HEBO). HEBO performs non-linear input and output warping, admits exact marginal log-likelihood optimisation and is robust to the values of learned parameters. We demonstrate HEBO's empirical efficacy on the NeurIPS 2020 Black-Box Optimisati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.03826","kind":"arxiv","version":6},"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/2012.03826/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":"2026-07-05T04:26:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GGRiHdvgqmPG3NPo73aKm1ATyVVz77tGic32q+xqIHFtJX4kaV5Mg7aB7FsyMAiWdXK947iK/IdeYyosulihBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T07:56:23.955594Z"},"content_sha256":"b08c0572187e6645c59db37175ef86e3dfdc5137b4827f8c9d88ef8926b0def2","schema_version":"1.0","event_id":"sha256:b08c0572187e6645c59db37175ef86e3dfdc5137b4827f8c9d88ef8926b0def2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6YXPVLXIBKABQIIOOGIHJKENZE/bundle.json","state_url":"https://pith.science/pith/6YXPVLXIBKABQIIOOGIHJKENZE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6YXPVLXIBKABQIIOOGIHJKENZE/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":"2026-08-05T07:56:23Z","links":{"resolver":"https://pith.science/pith/6YXPVLXIBKABQIIOOGIHJKENZE","bundle":"https://pith.science/pith/6YXPVLXIBKABQIIOOGIHJKENZE/bundle.json","state":"https://pith.science/pith/6YXPVLXIBKABQIIOOGIHJKENZE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6YXPVLXIBKABQIIOOGIHJKENZE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6YXPVLXIBKABQIIOOGIHJKENZE","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":"7085386cea44a1f9f7f5656ddd6a3e5467e08024a3e3d883c7c3808414479628","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-07T16:21:12Z","title_canon_sha256":"f9123af09792727d3c47d92fe4877d0a4d43beef2bb66644c421777c5ff04a41"},"schema_version":"1.0","source":{"id":"2012.03826","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.03826","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"arxiv_version","alias_value":"2012.03826v6","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.03826","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"pith_short_12","alias_value":"6YXPVLXIBKAB","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"pith_short_16","alias_value":"6YXPVLXIBKABQIIO","created_at":"2026-07-05T04:26:18Z"},{"alias_kind":"pith_short_8","alias_value":"6YXPVLXI","created_at":"2026-07-05T04:26:18Z"}],"graph_snapshots":[{"event_id":"sha256:b08c0572187e6645c59db37175ef86e3dfdc5137b4827f8c9d88ef8926b0def2","target":"graph","created_at":"2026-07-05T04:26:18Z","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/2012.03826/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work we rigorously analyse assumptions inherent to black-box optimisation hyper-parameter tuning tasks. Our results on the Bayesmark benchmark indicate that heteroscedasticity and non-stationarity pose significant challenges for black-box optimisers. Based on these findings, we propose a Heteroscedastic and Evolutionary Bayesian Optimisation solver (HEBO). HEBO performs non-linear input and output warping, admits exact marginal log-likelihood optimisation and is robust to the values of learned parameters. We demonstrate HEBO's empirical efficacy on the NeurIPS 2020 Black-Box Optimisati","authors_text":"Alexander I. Cowen-Rivers, Alexandre Max Maraval, Antoine Grosnit, Haitham Bou Ammar, Hao Jianye, Jan Peters, Jun Wang, Rasul Tutunov, Ryan Rhys Griffiths, Wenlong Lyu, Zhi Wang","cross_cats":["math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-07T16:21:12Z","title":"HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.03826","kind":"arxiv","version":6},"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:b86acbc66661deb0a82ee922316167434fa4ef1ff7268bc435ae689fd6e53260","target":"record","created_at":"2026-07-05T04:26:18Z","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":"7085386cea44a1f9f7f5656ddd6a3e5467e08024a3e3d883c7c3808414479628","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-07T16:21:12Z","title_canon_sha256":"f9123af09792727d3c47d92fe4877d0a4d43beef2bb66644c421777c5ff04a41"},"schema_version":"1.0","source":{"id":"2012.03826","kind":"arxiv","version":6}},"canonical_sha256":"f62efaaee80a8018210e719074a88dc93783d626b70eec631e1e3072676dfd28","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f62efaaee80a8018210e719074a88dc93783d626b70eec631e1e3072676dfd28","first_computed_at":"2026-07-05T04:26:18.595489Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:26:18.595489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FcS0TBVZoMMWASrwxwS+kRlGKEutZYbjBwkMPXym4nZskpFabtGYCwXMn0IEa2xoOJdmfmqlTgAkgSdYr8HQAA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:26:18.595999Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.03826","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b86acbc66661deb0a82ee922316167434fa4ef1ff7268bc435ae689fd6e53260","sha256:b08c0572187e6645c59db37175ef86e3dfdc5137b4827f8c9d88ef8926b0def2"],"state_sha256":"6471a518d8c47648913abe79142d6bf16858bdf2738ae6240ead72db526356e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bvsvY4uAYCrSfYdtzvTWkak05bUzpdg8oRt38jvPFcoNUT+Bd7yhxXinKsxQSxUyFse4NJ3Try4UnLIElkaPDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T07:56:23.959059Z","bundle_sha256":"fc9724414e33dedc8c580a1a09ad14686fa581f89d3be6fd9a42e643463f13dd"}}