{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:R5YL6BYTOUR3PHWJ5ZWNGXSFBZ","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":"cd57b606569cfbb875c39fee121216cc69b682668a7f96403f8f6a9dbe4ff12f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2024-02-05T17:22:34Z","title_canon_sha256":"85ad24cc0a593753c5de6c1c83b541937991321912c48bac0723dc77f328ac65"},"schema_version":"1.0","source":{"id":"2402.03210","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.03210","created_at":"2026-07-05T08:42:32Z"},{"alias_kind":"arxiv_version","alias_value":"2402.03210v2","created_at":"2026-07-05T08:42:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.03210","created_at":"2026-07-05T08:42:32Z"},{"alias_kind":"pith_short_12","alias_value":"R5YL6BYTOUR3","created_at":"2026-07-05T08:42:32Z"},{"alias_kind":"pith_short_16","alias_value":"R5YL6BYTOUR3PHWJ","created_at":"2026-07-05T08:42:32Z"},{"alias_kind":"pith_short_8","alias_value":"R5YL6BYT","created_at":"2026-07-05T08:42:32Z"}],"graph_snapshots":[{"event_id":"sha256:2705c460e12c005265d243561172cc4f621d1f00757b97e90d9c7d3ff55007dc","target":"graph","created_at":"2026-07-05T08:42:32Z","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/2402.03210/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We develop universal gradient methods for Stochastic Convex Optimization (SCO). Our algorithms automatically adapt not only to the oracle's noise but also to the H\\\"older smoothness of the objective function without a priori knowledge of the particular setting. The key ingredient is a novel strategy for adjusting step-size coefficients in the Stochastic Gradient Method (SGD). Unlike AdaGrad, which accumulates gradient norms, our Universal Gradient Method accumulates appropriate combinations of gradient- and iterate differences. The resulting algorithm has state-of-the-art worst-case convergenc","authors_text":"Ali Kavis, Anton Rodomanov, Kimon Antonakopoulos, Volkan Cevher, Yongtao Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2024-02-05T17:22:34Z","title":"Universal Gradient Methods for Stochastic Convex Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.03210","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":"sha256:7f35414ae9cd90ae400be6f9be99b4de7c6beab387b09a43f3940fd9aa437bf3","target":"record","created_at":"2026-07-05T08:42:32Z","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":"cd57b606569cfbb875c39fee121216cc69b682668a7f96403f8f6a9dbe4ff12f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2024-02-05T17:22:34Z","title_canon_sha256":"85ad24cc0a593753c5de6c1c83b541937991321912c48bac0723dc77f328ac65"},"schema_version":"1.0","source":{"id":"2402.03210","kind":"arxiv","version":2}},"canonical_sha256":"8f70bf07137523b79ec9ee6cd35e450e78c95110bcf7fc31cd8fd76c3bb29270","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8f70bf07137523b79ec9ee6cd35e450e78c95110bcf7fc31cd8fd76c3bb29270","first_computed_at":"2026-07-05T08:42:32.737949Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:42:32.737949Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MV5K8P7AThpjxiepSvyIvlcKZAncfZFVzVemNUHLVlRXwopefVpHT5B4SRojmV6WW480fRtJM/T7MerzTV4cDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:42:32.738435Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.03210","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7f35414ae9cd90ae400be6f9be99b4de7c6beab387b09a43f3940fd9aa437bf3","sha256:2705c460e12c005265d243561172cc4f621d1f00757b97e90d9c7d3ff55007dc"],"state_sha256":"4127c609740a09b69ceba96f8c2a5d280efc0aedcf759485fa9a7e4abcdf1d77"}