{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:ZIMFQNB7O7FNY62QDSCDATRKDO","short_pith_number":"pith:ZIMFQNB7","canonical_record":{"source":{"id":"1711.07511","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-20T19:39:48Z","cross_cats_sorted":["cs.LG","math.OC"],"title_canon_sha256":"92e4f5ca575b4807be81997210c1070f658739a75a47149b124204f5835eacb7","abstract_canon_sha256":"a8c868826e2c47d83c7edf19caab0c04efe3ab00302bfd4563cdcc1d211909c8"},"schema_version":"1.0"},"canonical_sha256":"ca1858343f77cadc7b501c84304e2a1b8b3745eb51a285959bfeb70737411c0e","source":{"kind":"arxiv","id":"1711.07511","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.07511","created_at":"2026-05-18T00:29:58Z"},{"alias_kind":"arxiv_version","alias_value":"1711.07511v1","created_at":"2026-05-18T00:29:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.07511","created_at":"2026-05-18T00:29:58Z"},{"alias_kind":"pith_short_12","alias_value":"ZIMFQNB7O7FN","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZIMFQNB7O7FNY62Q","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZIMFQNB7","created_at":"2026-05-18T12:31:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:ZIMFQNB7O7FNY62QDSCDATRKDO","target":"record","payload":{"canonical_record":{"source":{"id":"1711.07511","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-20T19:39:48Z","cross_cats_sorted":["cs.LG","math.OC"],"title_canon_sha256":"92e4f5ca575b4807be81997210c1070f658739a75a47149b124204f5835eacb7","abstract_canon_sha256":"a8c868826e2c47d83c7edf19caab0c04efe3ab00302bfd4563cdcc1d211909c8"},"schema_version":"1.0"},"canonical_sha256":"ca1858343f77cadc7b501c84304e2a1b8b3745eb51a285959bfeb70737411c0e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:58.835144Z","signature_b64":"lB2gkRk+gNSO3MPBv5dApaKzsSPpEYh6SJF72vIfrNt5mfrdBVPhAoZP5FpwwP2D2qUJ3RIl6Eypw2p7LQSIDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ca1858343f77cadc7b501c84304e2a1b8b3745eb51a285959bfeb70737411c0e","last_reissued_at":"2026-05-18T00:29:58.834669Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:58.834669Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.07511","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":"2026-05-18T00:29:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"augDgF+5nr+UbiaOdPtozVHzoVny3EazW6gmmf8YB4CyDKlmNOjSbbfyWSAl6dUOM76sqM7mBRfRHsu9l5fyCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T19:54:07.255943Z"},"content_sha256":"82a555620a1355b48b7b162becda8fdc01d6e8f3694c635f058b23830db8db14","schema_version":"1.0","event_id":"sha256:82a555620a1355b48b7b162becda8fdc01d6e8f3694c635f058b23830db8db14"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:ZIMFQNB7O7FNY62QDSCDATRKDO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimistic Robust Optimization With Applications To Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","math.OC"],"primary_cat":"stat.ML","authors_text":"Akiko Takeda, Alexander Mafusalov, Matthew Norton","submitted_at":"2017-11-20T19:39:48Z","abstract_excerpt":"Robust Optimization has traditionally taken a pessimistic, or worst-case viewpoint of uncertainty which is motivated by a desire to find sets of optimal policies that maintain feasibility under a variety of operating conditions. In this paper, we explore an optimistic, or best-case view of uncertainty and show that it can be a fruitful approach. We show that these techniques can be used to address a wide variety of problems. First, we apply our methods in the context of robust linear programming, providing a method for reducing conservatism in intuitive ways that encode economically realistic "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.07511","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":""},"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":"2026-05-18T00:29:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2vHXZFsoIvrPOD/WaGFlzhJi1nMWPqMgWp1MifZsfogMy8ekK3dmM03NFZh0HPSRAsFixJz6JHr1LiMBTNXGCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T19:54:07.256291Z"},"content_sha256":"a56a32062f5556f03e44284d3b0c21ec8600dbf08be940478ea6652b479b54b7","schema_version":"1.0","event_id":"sha256:a56a32062f5556f03e44284d3b0c21ec8600dbf08be940478ea6652b479b54b7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZIMFQNB7O7FNY62QDSCDATRKDO/bundle.json","state_url":"https://pith.science/pith/ZIMFQNB7O7FNY62QDSCDATRKDO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZIMFQNB7O7FNY62QDSCDATRKDO/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":"2026-05-21T19:54:07Z","links":{"resolver":"https://pith.science/pith/ZIMFQNB7O7FNY62QDSCDATRKDO","bundle":"https://pith.science/pith/ZIMFQNB7O7FNY62QDSCDATRKDO/bundle.json","state":"https://pith.science/pith/ZIMFQNB7O7FNY62QDSCDATRKDO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZIMFQNB7O7FNY62QDSCDATRKDO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ZIMFQNB7O7FNY62QDSCDATRKDO","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":"a8c868826e2c47d83c7edf19caab0c04efe3ab00302bfd4563cdcc1d211909c8","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-20T19:39:48Z","title_canon_sha256":"92e4f5ca575b4807be81997210c1070f658739a75a47149b124204f5835eacb7"},"schema_version":"1.0","source":{"id":"1711.07511","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.07511","created_at":"2026-05-18T00:29:58Z"},{"alias_kind":"arxiv_version","alias_value":"1711.07511v1","created_at":"2026-05-18T00:29:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.07511","created_at":"2026-05-18T00:29:58Z"},{"alias_kind":"pith_short_12","alias_value":"ZIMFQNB7O7FN","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZIMFQNB7O7FNY62Q","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZIMFQNB7","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:a56a32062f5556f03e44284d3b0c21ec8600dbf08be940478ea6652b479b54b7","target":"graph","created_at":"2026-05-18T00:29:58Z","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"},"paper":{"abstract_excerpt":"Robust Optimization has traditionally taken a pessimistic, or worst-case viewpoint of uncertainty which is motivated by a desire to find sets of optimal policies that maintain feasibility under a variety of operating conditions. In this paper, we explore an optimistic, or best-case view of uncertainty and show that it can be a fruitful approach. We show that these techniques can be used to address a wide variety of problems. First, we apply our methods in the context of robust linear programming, providing a method for reducing conservatism in intuitive ways that encode economically realistic ","authors_text":"Akiko Takeda, Alexander Mafusalov, Matthew Norton","cross_cats":["cs.LG","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-20T19:39:48Z","title":"Optimistic Robust Optimization With Applications To Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.07511","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":"sha256:82a555620a1355b48b7b162becda8fdc01d6e8f3694c635f058b23830db8db14","target":"record","created_at":"2026-05-18T00:29:58Z","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":"a8c868826e2c47d83c7edf19caab0c04efe3ab00302bfd4563cdcc1d211909c8","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-20T19:39:48Z","title_canon_sha256":"92e4f5ca575b4807be81997210c1070f658739a75a47149b124204f5835eacb7"},"schema_version":"1.0","source":{"id":"1711.07511","kind":"arxiv","version":1}},"canonical_sha256":"ca1858343f77cadc7b501c84304e2a1b8b3745eb51a285959bfeb70737411c0e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ca1858343f77cadc7b501c84304e2a1b8b3745eb51a285959bfeb70737411c0e","first_computed_at":"2026-05-18T00:29:58.834669Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:58.834669Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lB2gkRk+gNSO3MPBv5dApaKzsSPpEYh6SJF72vIfrNt5mfrdBVPhAoZP5FpwwP2D2qUJ3RIl6Eypw2p7LQSIDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:58.835144Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.07511","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82a555620a1355b48b7b162becda8fdc01d6e8f3694c635f058b23830db8db14","sha256:a56a32062f5556f03e44284d3b0c21ec8600dbf08be940478ea6652b479b54b7"],"state_sha256":"852a3538c58451cafb08be67903e15d25f15caf8542abd167878ab3e0cd77b9e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WtHKoTYT7xpmcJnnG5TADeuhnalxkBUfaQsxxMMcIYKD9ZttZyQxnIn2Nl6hA4ygU2t+M7cHchahrafZifbHDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T19:54:07.258541Z","bundle_sha256":"839891926526aeb4dd37104bfbb53a0109679853520527c7709053a8b17aff15"}}