{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:C2AYWP55O6LEMG55NWT6EYY7TS","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":"e3f2ee4cd0cd83bba88cf0552c99c690817a6aa223cb4fa0dddce30f564a4ba8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-10T16:12:32Z","title_canon_sha256":"bbba5286c5b735cbcd643984f084b44d461a7ff0ec62731f5f6defc18bbc6008"},"schema_version":"1.0","source":{"id":"2406.06420","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.06420","created_at":"2026-07-05T09:31:30Z"},{"alias_kind":"arxiv_version","alias_value":"2406.06420v2","created_at":"2026-07-05T09:31:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.06420","created_at":"2026-07-05T09:31:30Z"},{"alias_kind":"pith_short_12","alias_value":"C2AYWP55O6LE","created_at":"2026-07-05T09:31:30Z"},{"alias_kind":"pith_short_16","alias_value":"C2AYWP55O6LEMG55","created_at":"2026-07-05T09:31:30Z"},{"alias_kind":"pith_short_8","alias_value":"C2AYWP55","created_at":"2026-07-05T09:31:30Z"}],"graph_snapshots":[{"event_id":"sha256:f7959e17df5e52c0f6cc2b545f65f3ec3d64cc034b861f9c0506ed0677abc078","target":"graph","created_at":"2026-07-05T09:31:30Z","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/2406.06420/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Approximate Natural Gradient Descent (NGD) methods are an important family of optimisers for deep learning models, which use approximate Fisher information matrices to pre-condition gradients during training. The empirical Fisher (EF) method approximates the Fisher information matrix empirically by reusing the per-sample gradients collected during back-propagation. Despite its ease of implementation, the EF approximation has its theoretical and practical limitations. This paper investigates the inversely-scaled projection issue of EF, which is shown to be a major cause of its poor empirical ap","authors_text":"Chao Zhang, Philip Woodland, Wenyi Yu, Xiaodong Wu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-10T16:12:32Z","title":"An Improved Empirical Fisher Approximation for Natural Gradient Descent"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.06420","kind":"arxiv","version":2},"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":"sha256:1c9062937d09b1726c2ab02d18d2aa991be0d0ecec76e2e098dfb96c96285f62","target":"record","created_at":"2026-07-05T09:31:30Z","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":"e3f2ee4cd0cd83bba88cf0552c99c690817a6aa223cb4fa0dddce30f564a4ba8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-10T16:12:32Z","title_canon_sha256":"bbba5286c5b735cbcd643984f084b44d461a7ff0ec62731f5f6defc18bbc6008"},"schema_version":"1.0","source":{"id":"2406.06420","kind":"arxiv","version":2}},"canonical_sha256":"16818b3fbd7796461bbd6da7e2631f9c9bb9ed9bb476d065ca920f8288a3e61a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16818b3fbd7796461bbd6da7e2631f9c9bb9ed9bb476d065ca920f8288a3e61a","first_computed_at":"2026-07-05T09:31:30.048886Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:31:30.048886Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"H7CVV0DKHrihgkGT2Jm1FC5gk3PQDwIAzzLO4F8Xm1dSXdx6uHO9dNqCxOttHvJyZxHTIW3PLzSbQxPY4V33AA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:31:30.049390Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.06420","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c9062937d09b1726c2ab02d18d2aa991be0d0ecec76e2e098dfb96c96285f62","sha256:f7959e17df5e52c0f6cc2b545f65f3ec3d64cc034b861f9c0506ed0677abc078"],"state_sha256":"637a9d836e8f4ab8c2b96c8ee5c0352fcc920f7ae2993b12f322651c6711153b"}