{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:COOO7FIPKJF4NAMFN6VKZNE776","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":"32018c61c22cc05b232c6559aa50efef645a57545e1efcbddbc5a4d0a3469a9a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-25T09:42:42Z","title_canon_sha256":"b309489053892c552cfd24eb3e6300446e76d4aa20ae75e7775f39faff8616f6"},"schema_version":"1.0","source":{"id":"2411.16229","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.16229","created_at":"2026-07-05T11:45:30Z"},{"alias_kind":"arxiv_version","alias_value":"2411.16229v2","created_at":"2026-07-05T11:45:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.16229","created_at":"2026-07-05T11:45:30Z"},{"alias_kind":"pith_short_12","alias_value":"COOO7FIPKJF4","created_at":"2026-07-05T11:45:30Z"},{"alias_kind":"pith_short_16","alias_value":"COOO7FIPKJF4NAMF","created_at":"2026-07-05T11:45:30Z"},{"alias_kind":"pith_short_8","alias_value":"COOO7FIP","created_at":"2026-07-05T11:45:30Z"}],"graph_snapshots":[{"event_id":"sha256:8e55bd1c3fe14f91c6be0004c50eb565e7f2aa1a075309aefb1a0f8e2076266f","target":"graph","created_at":"2026-07-05T11:45:30Z","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/2411.16229/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Extreme Learning Machine (ELM) is a growing statistical technique widely applied to regression problems. In essence, ELMs are single-layer neural networks where the hidden layer weights are randomly sampled from a specific distribution, while the output layer weights are learned from the data. Two of the key challenges with this approach are the architecture design, specifically determining the optimal number of neurons in the hidden layer, and the method's sensitivity to the random initialization of hidden layer weights.\n  This paper introduces a new and enhanced learning algorithm for re","authors_text":"Daniela De Canditiis, Fabiano Veglianti","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-25T09:42:42Z","title":"Effective Non-Random Extreme Learning Machine"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.16229","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":"sha256:32fa889d6ba2426bf725c817a68c5b988f2f3eae8ec869d0fddbfa5383768334","target":"record","created_at":"2026-07-05T11:45:30Z","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":"32018c61c22cc05b232c6559aa50efef645a57545e1efcbddbc5a4d0a3469a9a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-25T09:42:42Z","title_canon_sha256":"b309489053892c552cfd24eb3e6300446e76d4aa20ae75e7775f39faff8616f6"},"schema_version":"1.0","source":{"id":"2411.16229","kind":"arxiv","version":2}},"canonical_sha256":"139cef950f524bc681856faaacb49fff96d060c98aacb5a5fdd5ba5818b4366c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"139cef950f524bc681856faaacb49fff96d060c98aacb5a5fdd5ba5818b4366c","first_computed_at":"2026-07-05T11:45:30.037264Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:30.037264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Gy9SRnmoDZiuy75IKWUCuVnAZEY1Vts8MXibi0fhMcRmo3b5sSP8sqElvkBslSLSBw+nkXdXQCNGfBeo7cBXDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:30.037770Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.16229","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32fa889d6ba2426bf725c817a68c5b988f2f3eae8ec869d0fddbfa5383768334","sha256:8e55bd1c3fe14f91c6be0004c50eb565e7f2aa1a075309aefb1a0f8e2076266f"],"state_sha256":"ac55cd3191fce7a2db907dede536bbe359b8a265972125f5a22eab45efb2de5a"}