{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:FJ25FZASBMALTRDIXOHM2KY5N4","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":"1c237a4c60b6b634d01089ddc96ca894146f88bc73f333a304ce519bb3dd7fc4","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-03-02T16:19:33Z","title_canon_sha256":"c059a7fccdaac6ca0e19dfb6b3bd90486229db3a00139645074b6ffbdb567fe3"},"schema_version":"1.0","source":{"id":"2003.00992","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.00992","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"arxiv_version","alias_value":"2003.00992v3","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.00992","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_12","alias_value":"FJ25FZASBMAL","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_16","alias_value":"FJ25FZASBMALTRDI","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_8","alias_value":"FJ25FZAS","created_at":"2026-07-05T01:27:21Z"}],"graph_snapshots":[{"event_id":"sha256:6ec983b0fc5679c52133b98686fa65f675867f86f71059ebfe22d7778d3e33a6","target":"graph","created_at":"2026-07-05T01:27:21Z","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/2003.00992/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a novel regularization approach for deep learning that incorporates and respects the underlying graphical structure of the neural network. Existing regularization methods often focus on dropping/penalizing weights in a global manner that ignores the connectivity structure of the neural network. We propose to use the Fiedler value of the neural network's underlying graph as a tool for regularization. We provide theoretical support for this approach via spectral graph theory. We list several useful properties of the Fiedler value that makes it suitable in regularization. We provide ","authors_text":"David Dunson, Edric Tam","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-03-02T16:19:33Z","title":"Fiedler Regularization: Learning Neural Networks with Graph Sparsity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.00992","kind":"arxiv","version":3},"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":"sha256:9230eae499f17fc4d7c48771c66e2176959a4b6016f15cedfd13cf69cd429cad","target":"record","created_at":"2026-07-05T01:27:21Z","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":"1c237a4c60b6b634d01089ddc96ca894146f88bc73f333a304ce519bb3dd7fc4","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-03-02T16:19:33Z","title_canon_sha256":"c059a7fccdaac6ca0e19dfb6b3bd90486229db3a00139645074b6ffbdb567fe3"},"schema_version":"1.0","source":{"id":"2003.00992","kind":"arxiv","version":3}},"canonical_sha256":"2a75d2e4120b00b9c468bb8ecd2b1d6f2690db09af6b6e39857ed40f8377297d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a75d2e4120b00b9c468bb8ecd2b1d6f2690db09af6b6e39857ed40f8377297d","first_computed_at":"2026-07-05T01:27:21.593969Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:27:21.593969Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6TncJKNLJy74czvJkcImFK6LLybPmYd9RIfUMzWaguqoXgsOxrBBsehrkgDnWmD3kypZAU+mv1jJe23D7zQrAA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:27:21.594461Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.00992","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9230eae499f17fc4d7c48771c66e2176959a4b6016f15cedfd13cf69cd429cad","sha256:6ec983b0fc5679c52133b98686fa65f675867f86f71059ebfe22d7778d3e33a6"],"state_sha256":"92a2cdac68eb3577cacf7335a6cd380e8c72af51851aabe6ad323bbbb4f5d0ad"}