{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:7BH7FOJXKJL5AEHPKJQ6ATNNF3","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":"373609debffe680f45aa4516b3e7caed993f7590e1f52456dc3dc498921af619","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-03-12T11:12:48Z","title_canon_sha256":"547e38e34231fac0adaaf8300377973b9c3a90576560ab2387bdf2f4f5acdfd8"},"schema_version":"1.0","source":{"id":"1803.04193","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.04193","created_at":"2026-05-18T00:21:19Z"},{"alias_kind":"arxiv_version","alias_value":"1803.04193v1","created_at":"2026-05-18T00:21:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.04193","created_at":"2026-05-18T00:21:19Z"},{"alias_kind":"pith_short_12","alias_value":"7BH7FOJXKJL5","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7BH7FOJXKJL5AEHP","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7BH7FOJX","created_at":"2026-05-18T12:32:11Z"}],"graph_snapshots":[{"event_id":"sha256:da50b15753442ef69ddc075d2c5ab378334cc7e5e79afb54510793f80c71ec3f","target":"graph","created_at":"2026-05-18T00:21:19Z","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"},"paper":{"abstract_excerpt":"In this article, we improve extreme learning machines for regression tasks using a graph signal processing based regularization. We assume that the target signal for prediction or regression is a graph signal. With this assumption, we use the regularization to enforce that the output of an extreme learning machine is smooth over a given graph. Simulation results with real data confirm that such regularization helps significantly when the available training data is limited in size and corrupted by noise.","authors_text":"Arun Venkitaraman, Peter H\\\"andel, Saikat Chatterjee","cross_cats":["cs.LG","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-03-12T11:12:48Z","title":"Extreme Learning Machine for Graph Signal Processing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.04193","kind":"arxiv","version":1},"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":"sha256:16a63ad60f939aca9930a62ba8a3ba05aa638c4e7d5de66af2d591fea5bcc23c","target":"record","created_at":"2026-05-18T00:21:19Z","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":"373609debffe680f45aa4516b3e7caed993f7590e1f52456dc3dc498921af619","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-03-12T11:12:48Z","title_canon_sha256":"547e38e34231fac0adaaf8300377973b9c3a90576560ab2387bdf2f4f5acdfd8"},"schema_version":"1.0","source":{"id":"1803.04193","kind":"arxiv","version":1}},"canonical_sha256":"f84ff2b9375257d010ef5261e04dad2ef8b08aa0f9b0cc407196fdb3835c16c7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f84ff2b9375257d010ef5261e04dad2ef8b08aa0f9b0cc407196fdb3835c16c7","first_computed_at":"2026-05-18T00:21:19.179250Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:21:19.179250Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"J9B9BSseBD97XsjxyYyiAcjDQtBFnZuHsDxaU+lLRFkZnDEFBovSzD6P3a9ywazG69bKiqpaPcFKHSyD8aaKDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:21:19.180800Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.04193","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16a63ad60f939aca9930a62ba8a3ba05aa638c4e7d5de66af2d591fea5bcc23c","sha256:da50b15753442ef69ddc075d2c5ab378334cc7e5e79afb54510793f80c71ec3f"],"state_sha256":"8284b368804de95c34decdde81097e03dffaf526a4fb9be3538c4143d71e7324"}