{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:O2E7MJQNMDVOKUKTAG7JWNMEAB","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":"8d4e1478a1a19f3646099a06d3684e167b2ca8d3c3a6aaece23775cc632b7530","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-14T14:23:03Z","title_canon_sha256":"d6657741e647e84aee89ee0691ec8dc8e0eb4531fff389e0ba509ff38d992ca4"},"schema_version":"1.0","source":{"id":"2608.14336","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.14336","created_at":"2026-08-17T01:13:23Z"},{"alias_kind":"arxiv_version","alias_value":"2608.14336v1","created_at":"2026-08-17T01:13:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.14336","created_at":"2026-08-17T01:13:23Z"},{"alias_kind":"pith_short_12","alias_value":"O2E7MJQNMDVO","created_at":"2026-08-17T01:13:23Z"},{"alias_kind":"pith_short_16","alias_value":"O2E7MJQNMDVOKUKT","created_at":"2026-08-17T01:13:23Z"},{"alias_kind":"pith_short_8","alias_value":"O2E7MJQN","created_at":"2026-08-17T01:13:23Z"}],"graph_snapshots":[{"event_id":"sha256:a7fb153cd18cd8ac587b5dfde24f26dc647af58c0b0ff9750420f6132e7b9c1b","target":"graph","created_at":"2026-08-17T01:13:23Z","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/2608.14336/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Wasserstein distributionally robust optimization (DRO) is a versatile and widely adopted framework for decision-making under uncertainty, yet its standard deterministic reformulations generally contain non-convex inner subproblems that are challenging to solve. To address this issue, we propose a shrinkage path heuristic that reduces the solution of a DRO problem to a one-dimensional search over the line segment connecting the (typically benign) sample average approximation (SAA) and the (more demanding but practically solvable) classical robust optimization solution. We derive a priori subopt","authors_text":"Lingjun Meng, Ryan Cory-Wright, Wolfram Wiesemann","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-14T14:23:03Z","title":"A Shrinkage Path Heuristic for Wasserstein Distributionally Robust Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.14336","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:c60348771338532915387b8f0f3baa64f34f7667ad022604204e9dd73a728632","target":"record","created_at":"2026-08-17T01:13:23Z","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":"8d4e1478a1a19f3646099a06d3684e167b2ca8d3c3a6aaece23775cc632b7530","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2026-08-14T14:23:03Z","title_canon_sha256":"d6657741e647e84aee89ee0691ec8dc8e0eb4531fff389e0ba509ff38d992ca4"},"schema_version":"1.0","source":{"id":"2608.14336","kind":"arxiv","version":1}},"canonical_sha256":"7689f6260d60eae5515301be9b3584004d5c105da4b012316d667d1aad732644","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7689f6260d60eae5515301be9b3584004d5c105da4b012316d667d1aad732644","first_computed_at":"2026-08-17T01:13:23.448192Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-17T01:13:23.448192Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"22OmuPHlFvpmNjVD0iv1I5ASZcAqeTRKqKjLfmD0pGiVqPXnE5O+Qyx++XqgYvSc7cdhJsNJ26NLtiMV9BejDg==","signature_status":"signed_v1","signed_at":"2026-08-17T01:13:23.450501Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.14336","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c60348771338532915387b8f0f3baa64f34f7667ad022604204e9dd73a728632","sha256:a7fb153cd18cd8ac587b5dfde24f26dc647af58c0b0ff9750420f6132e7b9c1b"],"state_sha256":"c94e4cae30bba4185cd618144fce2d948e3010f06e80c4ed74787b7814cc8855"}