{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:S6SC7QT7LKENVPETWJNB7BDNPP","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":"78ce670df9c1c2e94d5c5949ee87d063a16af6d3a25a22d40cc2007c2e139345","cross_cats_sorted":["cs.DC","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-26T00:32:31Z","title_canon_sha256":"f90c19f663b933cc1f1b28cd11ef49e002f954e8f92495469aa624f7482a5eab"},"schema_version":"1.0","source":{"id":"1802.09113","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.09113","created_at":"2026-05-18T00:22:02Z"},{"alias_kind":"arxiv_version","alias_value":"1802.09113v2","created_at":"2026-05-18T00:22:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.09113","created_at":"2026-05-18T00:22:02Z"},{"alias_kind":"pith_short_12","alias_value":"S6SC7QT7LKEN","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"S6SC7QT7LKENVPET","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"S6SC7QT7","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:fdeb589ac1b09eb59dce305a29acaf837b5bc779791c016e2dba40572da2532e","target":"graph","created_at":"2026-05-18T00:22:02Z","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":"First order methods, which solely rely on gradient information, are commonly used in diverse machine learning (ML) and data analysis (DA) applications. This is attributed to the simplicity of their implementations, as well as low per-iteration computational/storage costs. However, they suffer from significant disadvantages; most notably, their performance degrades with increasing problem ill-conditioning. Furthermore, they often involve a large number of hyper-parameters, and are notoriously sensitive to parameters such as the step-size. By incorporating additional information from the Hessian","authors_text":"Ananth Grama, Farbod Roosta-Khorasani, Michael W. Mahoney, Sudhir B. Kylasa","cross_cats":["cs.DC","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-26T00:32:31Z","title":"GPU Accelerated Sub-Sampled Newton's Method"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.09113","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":"sha256:8e9aae290be4bee52b4ba439d93e996424c14b78633f7ce392793014f37889d7","target":"record","created_at":"2026-05-18T00:22:02Z","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":"78ce670df9c1c2e94d5c5949ee87d063a16af6d3a25a22d40cc2007c2e139345","cross_cats_sorted":["cs.DC","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-26T00:32:31Z","title_canon_sha256":"f90c19f663b933cc1f1b28cd11ef49e002f954e8f92495469aa624f7482a5eab"},"schema_version":"1.0","source":{"id":"1802.09113","kind":"arxiv","version":2}},"canonical_sha256":"97a42fc27f5a88dabc93b25a1f846d7bf32bb9b20116a35929574d6fe5890748","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97a42fc27f5a88dabc93b25a1f846d7bf32bb9b20116a35929574d6fe5890748","first_computed_at":"2026-05-18T00:22:02.112805Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:22:02.112805Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dFp7+qHEf1ZFCavbCp+QnKdEsSJkXHm01+9/lPKkfU7kN16oXyLuS7yJtnlvdICP4FMHAlZkiEse2sdN4KG9Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:22:02.113405Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.09113","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8e9aae290be4bee52b4ba439d93e996424c14b78633f7ce392793014f37889d7","sha256:fdeb589ac1b09eb59dce305a29acaf837b5bc779791c016e2dba40572da2532e"],"state_sha256":"b3c2cd133453782ef7b6bcd8b5c59530cf78c51877efada2b48b2822b2c06b9a"}