{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:S6V27YH7WSPF3XYPKP3F6VHJO2","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":"a91ee69bb9aedcec1fb3bb67b9c402437a582ac4764ae591209766c5a2f0b658","cross_cats_sorted":["cs.DS","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-03-24T17:31:43Z","title_canon_sha256":"3e092771a3fdc4bf630940e2eb96a1664c1c18a14c0a8d38ec9784d5abc1fc4d"},"schema_version":"1.0","source":{"id":"2203.13225","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.13225","created_at":"2026-07-05T04:08:21Z"},{"alias_kind":"arxiv_version","alias_value":"2203.13225v1","created_at":"2026-07-05T04:08:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.13225","created_at":"2026-07-05T04:08:21Z"},{"alias_kind":"pith_short_12","alias_value":"S6V27YH7WSPF","created_at":"2026-07-05T04:08:21Z"},{"alias_kind":"pith_short_16","alias_value":"S6V27YH7WSPF3XYP","created_at":"2026-07-05T04:08:21Z"},{"alias_kind":"pith_short_8","alias_value":"S6V27YH7","created_at":"2026-07-05T04:08:21Z"}],"graph_snapshots":[{"event_id":"sha256:a0e988a4f3150c9a13216181b3b8dad94679231c3644a511eedfd22519c6fa0f","target":"graph","created_at":"2026-07-05T04:08:21Z","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/2203.13225/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We develop and analyze algorithms for distributionally robust optimization (DRO) of convex losses. In particular, we consider group-structured and bounded $f$-divergence uncertainty sets. Our approach relies on an accelerated method that queries a ball optimization oracle, i.e., a subroutine that minimizes the objective within a small ball around the query point. Our main contribution is efficient implementations of this oracle for DRO objectives. For DRO with $N$ non-smooth loss functions, the resulting algorithms find an $\\epsilon$-accurate solution with $\\widetilde{O}\\left(N\\epsilon^{-2/3} ","authors_text":"Danielle Hausler, Yair Carmon","cross_cats":["cs.DS","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-03-24T17:31:43Z","title":"Distributionally Robust Optimization via Ball Oracle Acceleration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.13225","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:a081f5a02416e348ad7666afa24116c33cb3f107a60246c836f42a2dd0253486","target":"record","created_at":"2026-07-05T04:08:21Z","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":"a91ee69bb9aedcec1fb3bb67b9c402437a582ac4764ae591209766c5a2f0b658","cross_cats_sorted":["cs.DS","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-03-24T17:31:43Z","title_canon_sha256":"3e092771a3fdc4bf630940e2eb96a1664c1c18a14c0a8d38ec9784d5abc1fc4d"},"schema_version":"1.0","source":{"id":"2203.13225","kind":"arxiv","version":1}},"canonical_sha256":"97abafe0ffb49e5ddf0f53f65f54e976822066b7b2d3b50e1bce4b72181bd000","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97abafe0ffb49e5ddf0f53f65f54e976822066b7b2d3b50e1bce4b72181bd000","first_computed_at":"2026-07-05T04:08:21.988742Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:08:21.988742Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lJIpPJ3ShKnagktm5qd/m970cZ5TPt3dUvEMuDtD67VsVJBX+zhQvXi9BszsTX+uDf2XU00nDDRheYa/8FS2AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:08:21.989149Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.13225","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a081f5a02416e348ad7666afa24116c33cb3f107a60246c836f42a2dd0253486","sha256:a0e988a4f3150c9a13216181b3b8dad94679231c3644a511eedfd22519c6fa0f"],"state_sha256":"760d53b4fe2e87555fad2c44c5d70a4f203d01c92cffb2a034b3f2434db377a1"}