{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:P7FS3OF6PYMN5ZPLSLQFITDV7I","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":"c19ef0bb84e44b8a17d1ee6edd25b933fbe6646ee2a6cb37d312a7af80b16451","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-20T12:24:49Z","title_canon_sha256":"57ddcdab0da238108c4722272344756caada8d12d781f1c2a9c06696a4848957"},"schema_version":"1.0","source":{"id":"2304.10255","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.10255","created_at":"2026-06-02T02:04:03Z"},{"alias_kind":"arxiv_version","alias_value":"2304.10255v4","created_at":"2026-06-02T02:04:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.10255","created_at":"2026-06-02T02:04:03Z"},{"alias_kind":"pith_short_12","alias_value":"P7FS3OF6PYMN","created_at":"2026-06-02T02:04:03Z"},{"alias_kind":"pith_short_16","alias_value":"P7FS3OF6PYMN5ZPL","created_at":"2026-06-02T02:04:03Z"},{"alias_kind":"pith_short_8","alias_value":"P7FS3OF6","created_at":"2026-06-02T02:04:03Z"}],"graph_snapshots":[{"event_id":"sha256:7ad37f047788b7c68680345a3d61a3144b443da4ec1d8e74e0ec91dcdf31d0d8","target":"graph","created_at":"2026-06-02T02:04:03Z","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/2304.10255/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The recent rise in popularity of Hyperparameter Optimization (HPO) for deep learning has highlighted the role that good hyperparameter (HP) space design can play in training strong models. In turn, designing a good HP space is critically dependent on understanding the role of different HPs. This motivates research on HP Importance (HPI), e.g., with the popular method of functional ANOVA (f-ANOVA). However, the original f-ANOVA formulation is inapplicable to the subspaces most relevant to algorithm designers, such as those defined by top performance. To overcome this issue, we derive a novel fo","authors_text":"Archit Bansal, Frank Hutter, Shuhei Watanabe","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-20T12:24:49Z","title":"PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.10255","kind":"arxiv","version":4},"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":"sha256:9b89f4468534816dfee041f0b43d9b1e087942e153a34d3cfe11120c0bc24b63","target":"record","created_at":"2026-06-02T02:04:03Z","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":"c19ef0bb84e44b8a17d1ee6edd25b933fbe6646ee2a6cb37d312a7af80b16451","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-20T12:24:49Z","title_canon_sha256":"57ddcdab0da238108c4722272344756caada8d12d781f1c2a9c06696a4848957"},"schema_version":"1.0","source":{"id":"2304.10255","kind":"arxiv","version":4}},"canonical_sha256":"7fcb2db8be7e18dee5eb92e0544c75fa202c741c069bdd66e7b8c4b5096debc2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7fcb2db8be7e18dee5eb92e0544c75fa202c741c069bdd66e7b8c4b5096debc2","first_computed_at":"2026-06-02T02:04:03.590611Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T02:04:03.590611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/i+goum2j9KwJ6pOJGH/ZcMMS1vbqP5JKc+p8HYejD2MgxmIgFzanrSdv/E37JHFZF3LVZ/BGw7ryRh0OYO6Ag==","signature_status":"signed_v1","signed_at":"2026-06-02T02:04:03.591080Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.10255","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9b89f4468534816dfee041f0b43d9b1e087942e153a34d3cfe11120c0bc24b63","sha256:7ad37f047788b7c68680345a3d61a3144b443da4ec1d8e74e0ec91dcdf31d0d8"],"state_sha256":"89d11b397498216bbc312880c4e9fcdfd62f64234aa301f219a48ec3d683be62"}