{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:HCEQ3UUCVYXCEM537WMSGW273X","short_pith_number":"pith:HCEQ3UUC","canonical_record":{"source":{"id":"2003.00248","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-02-29T12:24:56Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"b1312dc75b949f4d1a628df69f0a6fc33a67501d0e469ac2b2201522faeb2191","abstract_canon_sha256":"4a57ab968a19ca0cc0e2155620ab479c014bbb853ad55ca729ad7a62efa87f0c"},"schema_version":"1.0"},"canonical_sha256":"38890dd282ae2e2233bbfd99235b5fddf33834c290a7da6b84831cc96c6a7154","source":{"kind":"arxiv","id":"2003.00248","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.00248","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"arxiv_version","alias_value":"2003.00248v1","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.00248","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"pith_short_12","alias_value":"HCEQ3UUCVYXC","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"pith_short_16","alias_value":"HCEQ3UUCVYXCEM53","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"pith_short_8","alias_value":"HCEQ3UUC","created_at":"2026-07-05T00:44:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:HCEQ3UUCVYXCEM537WMSGW273X","target":"record","payload":{"canonical_record":{"source":{"id":"2003.00248","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-02-29T12:24:56Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"b1312dc75b949f4d1a628df69f0a6fc33a67501d0e469ac2b2201522faeb2191","abstract_canon_sha256":"4a57ab968a19ca0cc0e2155620ab479c014bbb853ad55ca729ad7a62efa87f0c"},"schema_version":"1.0"},"canonical_sha256":"38890dd282ae2e2233bbfd99235b5fddf33834c290a7da6b84831cc96c6a7154","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:44:45.265017Z","signature_b64":"Il7vVZUF1Bu58MsqXMSnHkZEezUqcwxE6w/SsdJGi+CV2lnAaFdQQzGZt2TlPacIaceS6+qcafRmtRpSD0SxCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"38890dd282ae2e2233bbfd99235b5fddf33834c290a7da6b84831cc96c6a7154","last_reissued_at":"2026-07-05T00:44:45.264447Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:44:45.264447Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2003.00248","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:44:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G+pDtqnUmRoIPAGfddPzIlcQTrO2RNpyP7rxFXMv4fnGDs+6knLXTk4wXS5o6mvBvPKSZyWxYWGl0Wq8tMRYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:52:34.858442Z"},"content_sha256":"1b562c09d00d6dcd259cd4cb168f9761160cc6dbad7e9bb20ccb39de37e1829b","schema_version":"1.0","event_id":"sha256:1b562c09d00d6dcd259cd4cb168f9761160cc6dbad7e9bb20ccb39de37e1829b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:HCEQ3UUCVYXCEM537WMSGW273X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tightly Robust Optimization via Empirical Domain Reduction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"math.OC","authors_text":"Akihiro Yabe, Takanori Maehara","submitted_at":"2020-02-29T12:24:56Z","abstract_excerpt":"Data-driven decision-making is performed by solving a parameterized optimization problem, and the optimal decision is given by an optimal solution for unknown true parameters. We often need a solution that satisfies true constraints even though these are unknown. Robust optimization is employed to obtain such a solution, where the uncertainty of the parameter is represented by an ellipsoid, and the scale of robustness is controlled by a coefficient. In this study, we propose an algorithm to determine the scale such that the solution has a good objective value and satisfies the true constraints"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.00248","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2003.00248/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:44:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M/6OlxTDtu+mtjZIIDwEmdrD5bYI6sxWMN4+q+XGjugYIwSMsXqBLqgzqt/fjfIU3OBaVinHc+cBF4I+VTvNCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:52:34.858972Z"},"content_sha256":"09146d8eb0ea58c360a31a3ed0449bb92fb6f2784c508fcbd36c67d84b2eebc6","schema_version":"1.0","event_id":"sha256:09146d8eb0ea58c360a31a3ed0449bb92fb6f2784c508fcbd36c67d84b2eebc6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HCEQ3UUCVYXCEM537WMSGW273X/bundle.json","state_url":"https://pith.science/pith/HCEQ3UUCVYXCEM537WMSGW273X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HCEQ3UUCVYXCEM537WMSGW273X/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T14:52:34Z","links":{"resolver":"https://pith.science/pith/HCEQ3UUCVYXCEM537WMSGW273X","bundle":"https://pith.science/pith/HCEQ3UUCVYXCEM537WMSGW273X/bundle.json","state":"https://pith.science/pith/HCEQ3UUCVYXCEM537WMSGW273X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HCEQ3UUCVYXCEM537WMSGW273X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:HCEQ3UUCVYXCEM537WMSGW273X","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":"4a57ab968a19ca0cc0e2155620ab479c014bbb853ad55ca729ad7a62efa87f0c","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-02-29T12:24:56Z","title_canon_sha256":"b1312dc75b949f4d1a628df69f0a6fc33a67501d0e469ac2b2201522faeb2191"},"schema_version":"1.0","source":{"id":"2003.00248","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.00248","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"arxiv_version","alias_value":"2003.00248v1","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.00248","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"pith_short_12","alias_value":"HCEQ3UUCVYXC","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"pith_short_16","alias_value":"HCEQ3UUCVYXCEM53","created_at":"2026-07-05T00:44:45Z"},{"alias_kind":"pith_short_8","alias_value":"HCEQ3UUC","created_at":"2026-07-05T00:44:45Z"}],"graph_snapshots":[{"event_id":"sha256:09146d8eb0ea58c360a31a3ed0449bb92fb6f2784c508fcbd36c67d84b2eebc6","target":"graph","created_at":"2026-07-05T00:44:45Z","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/2003.00248/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data-driven decision-making is performed by solving a parameterized optimization problem, and the optimal decision is given by an optimal solution for unknown true parameters. We often need a solution that satisfies true constraints even though these are unknown. Robust optimization is employed to obtain such a solution, where the uncertainty of the parameter is represented by an ellipsoid, and the scale of robustness is controlled by a coefficient. In this study, we propose an algorithm to determine the scale such that the solution has a good objective value and satisfies the true constraints","authors_text":"Akihiro Yabe, Takanori Maehara","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-02-29T12:24:56Z","title":"Tightly Robust Optimization via Empirical Domain Reduction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.00248","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":"sha256:1b562c09d00d6dcd259cd4cb168f9761160cc6dbad7e9bb20ccb39de37e1829b","target":"record","created_at":"2026-07-05T00:44:45Z","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":"4a57ab968a19ca0cc0e2155620ab479c014bbb853ad55ca729ad7a62efa87f0c","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-02-29T12:24:56Z","title_canon_sha256":"b1312dc75b949f4d1a628df69f0a6fc33a67501d0e469ac2b2201522faeb2191"},"schema_version":"1.0","source":{"id":"2003.00248","kind":"arxiv","version":1}},"canonical_sha256":"38890dd282ae2e2233bbfd99235b5fddf33834c290a7da6b84831cc96c6a7154","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"38890dd282ae2e2233bbfd99235b5fddf33834c290a7da6b84831cc96c6a7154","first_computed_at":"2026-07-05T00:44:45.264447Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:44:45.264447Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Il7vVZUF1Bu58MsqXMSnHkZEezUqcwxE6w/SsdJGi+CV2lnAaFdQQzGZt2TlPacIaceS6+qcafRmtRpSD0SxCw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:44:45.265017Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.00248","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b562c09d00d6dcd259cd4cb168f9761160cc6dbad7e9bb20ccb39de37e1829b","sha256:09146d8eb0ea58c360a31a3ed0449bb92fb6f2784c508fcbd36c67d84b2eebc6"],"state_sha256":"e25d2bc5288a31df4d9712af38916e882e9ed1e356b83936c21aadaac812b35b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4CcpFeTJLnssR9PU6LvNjvdqqlfz1ik1hbkGRDEzBWndUW26zpJuF2EFvY+hSbkODoHAuSzI7lVTSs2CQbwCDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T14:52:34.862091Z","bundle_sha256":"d84e5c84bfa824ef40f032894b2d09c7d2966c59988ccf70a6233e7f663850b4"}}