{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:MSFXTGLY3IBLAAT4V36THQ4IPK","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":"14f167760a94741613bbb4fc7804b5eef73e3d9a5a111fd5472963b88b237323","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2022-11-14T21:54:31Z","title_canon_sha256":"43675812c9cf8440e7a390cd5b0785be8e9e20bdf010b5134ae434aed106a710"},"schema_version":"1.0","source":{"id":"2211.07767","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.07767","created_at":"2026-07-05T05:45:35Z"},{"alias_kind":"arxiv_version","alias_value":"2211.07767v3","created_at":"2026-07-05T05:45:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.07767","created_at":"2026-07-05T05:45:35Z"},{"alias_kind":"pith_short_12","alias_value":"MSFXTGLY3IBL","created_at":"2026-07-05T05:45:35Z"},{"alias_kind":"pith_short_16","alias_value":"MSFXTGLY3IBLAAT4","created_at":"2026-07-05T05:45:35Z"},{"alias_kind":"pith_short_8","alias_value":"MSFXTGLY","created_at":"2026-07-05T05:45:35Z"}],"graph_snapshots":[{"event_id":"sha256:ef56f05aff606648d1de2f98aa1cf82ccd742b885d129af0b7875c6398d241e7","target":"graph","created_at":"2026-07-05T05:45:35Z","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/2211.07767/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In real-world decision-making, uncertainty is important yet difficult to handle. Stochastic dominance provides a theoretically sound approach for comparing uncertain quantities, but optimization with stochastic dominance constraints is often computationally expensive, which limits practical applicability. In this paper, we develop a simple yet efficient approach for the problem, the Light Stochastic Dominance Solver (light-SD), that leverages useful properties of the Lagrangian. We recast the inner optimization in the Lagrangian as a learning problem for surrogate approximation, which bypasses","authors_text":"Bethany Wang, Bo Dai, Dale Schuurmans, Hanjun Dai, Na Li, Niao He, Yuan Xue","cross_cats":["cs.LG","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2022-11-14T21:54:31Z","title":"Learning to Optimize with Stochastic Dominance Constraints"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.07767","kind":"arxiv","version":3},"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:c9474706e12caf29601420cf2b71f945030d961d3a284ff8bcbe05b985f293a7","target":"record","created_at":"2026-07-05T05:45:35Z","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":"14f167760a94741613bbb4fc7804b5eef73e3d9a5a111fd5472963b88b237323","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2022-11-14T21:54:31Z","title_canon_sha256":"43675812c9cf8440e7a390cd5b0785be8e9e20bdf010b5134ae434aed106a710"},"schema_version":"1.0","source":{"id":"2211.07767","kind":"arxiv","version":3}},"canonical_sha256":"648b799978da02b0027caefd33c3887ab1addd41e5e106537b59da9461485a56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"648b799978da02b0027caefd33c3887ab1addd41e5e106537b59da9461485a56","first_computed_at":"2026-07-05T05:45:35.138943Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:45:35.138943Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"y7tDRr+K0ylhn9ReerhAHrSavisa68pSgQ51Y04lmisgbMi31gMxm7kpmnPE90rnCk5Z6MK55kalUYIHB+lKDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:45:35.139452Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.07767","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c9474706e12caf29601420cf2b71f945030d961d3a284ff8bcbe05b985f293a7","sha256:ef56f05aff606648d1de2f98aa1cf82ccd742b885d129af0b7875c6398d241e7"],"state_sha256":"ed1ad788a22bac149b0853cf17e8b8b56bcc1d11dd5e7cf4e40885b725c1c42d"}