{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:XPEZ2A6WR7SZYJ6OU44LH5JI7E","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":"e5654e6b01e48dfcdc0ae66b6fe33217ccde6383698f52444f45c8d799b0f649","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-06-17T02:16:51Z","title_canon_sha256":"75fa167696f380c1e135347ea39c5aa8666414cb427356c86ae88cedfd8af955"},"schema_version":"1.0","source":{"id":"2006.09606","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.09606","created_at":"2026-07-05T02:26:12Z"},{"alias_kind":"arxiv_version","alias_value":"2006.09606v2","created_at":"2026-07-05T02:26:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.09606","created_at":"2026-07-05T02:26:12Z"},{"alias_kind":"pith_short_12","alias_value":"XPEZ2A6WR7SZ","created_at":"2026-07-05T02:26:12Z"},{"alias_kind":"pith_short_16","alias_value":"XPEZ2A6WR7SZYJ6O","created_at":"2026-07-05T02:26:12Z"},{"alias_kind":"pith_short_8","alias_value":"XPEZ2A6W","created_at":"2026-07-05T02:26:12Z"}],"graph_snapshots":[{"event_id":"sha256:a6312b22208dca5eeaae230bca5f0d89c453e005a289d78be39fc360ddba5646","target":"graph","created_at":"2026-07-05T02:26:12Z","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/2006.09606/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we consider stochastic second-order methods for minimizing a finite summation of nonconvex functions. One important key is to find an ingenious but cheap scheme to incorporate local curvature information. Since the true Hessian matrix is often a combination of a cheap part and an expensive part, we propose a structured stochastic quasi-Newton method by using partial Hessian information as much as possible. By further exploiting either the low-rank structure or the kronecker-product properties of the quasi-Newton approximations, the computation of the quasi-Newton direction is af","authors_text":"Dong Xu, Hongyu Chen, Mengyun Chen, Minghan Yang, Zaiwen Wen","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-06-17T02:16:51Z","title":"Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.09606","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:e34ecf36b73e45df7c64407e49c82e1afbaff261c5ebe937ab7418e0ef2fbf32","target":"record","created_at":"2026-07-05T02:26:12Z","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":"e5654e6b01e48dfcdc0ae66b6fe33217ccde6383698f52444f45c8d799b0f649","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-06-17T02:16:51Z","title_canon_sha256":"75fa167696f380c1e135347ea39c5aa8666414cb427356c86ae88cedfd8af955"},"schema_version":"1.0","source":{"id":"2006.09606","kind":"arxiv","version":2}},"canonical_sha256":"bbc99d03d68fe59c27cea738b3f528f90025de5751e0389872c0d0c7ec35e088","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bbc99d03d68fe59c27cea738b3f528f90025de5751e0389872c0d0c7ec35e088","first_computed_at":"2026-07-05T02:26:12.312976Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:26:12.312976Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AV55SBGNZnsoJVYSUGfwccPMkT/MbUOiV3kCZQciHxwSbAjP8tS3vpJB9OTqWiHz/vLUnGJKGzqkx0izhaSBDw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:26:12.313478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.09606","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e34ecf36b73e45df7c64407e49c82e1afbaff261c5ebe937ab7418e0ef2fbf32","sha256:a6312b22208dca5eeaae230bca5f0d89c453e005a289d78be39fc360ddba5646"],"state_sha256":"762551e1548dfd8903ea1a89568646fb1429e258d5083c40c25a4425a2aca6e9"}