{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:YIJWXDTGPZDMMKQW7OCUWASMW7","short_pith_number":"pith:YIJWXDTG","canonical_record":{"source":{"id":"1708.07888","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-25T21:12:40Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"2333bf0f8e29f761f0a4bf90a3fef25532ef610ba221b23bc80586f3aac47643","abstract_canon_sha256":"be995229f33193b3f1caba2abcfe8ce164e1a10fd7028d4e0ade9ef41a3a822b"},"schema_version":"1.0"},"canonical_sha256":"c2136b8e667e46c62a16fb854b024cb7e2fb1128369e16bb6c987cc78719d772","source":{"kind":"arxiv","id":"1708.07888","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.07888","created_at":"2026-05-18T00:25:28Z"},{"alias_kind":"arxiv_version","alias_value":"1708.07888v3","created_at":"2026-05-18T00:25:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.07888","created_at":"2026-05-18T00:25:28Z"},{"alias_kind":"pith_short_12","alias_value":"YIJWXDTGPZDM","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YIJWXDTGPZDMMKQW","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YIJWXDTG","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:YIJWXDTGPZDMMKQW7OCUWASMW7","target":"record","payload":{"canonical_record":{"source":{"id":"1708.07888","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-25T21:12:40Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"2333bf0f8e29f761f0a4bf90a3fef25532ef610ba221b23bc80586f3aac47643","abstract_canon_sha256":"be995229f33193b3f1caba2abcfe8ce164e1a10fd7028d4e0ade9ef41a3a822b"},"schema_version":"1.0"},"canonical_sha256":"c2136b8e667e46c62a16fb854b024cb7e2fb1128369e16bb6c987cc78719d772","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:28.893131Z","signature_b64":"VhqX+z54Ve6ig48TPsBv1mkKxarM7Y3QjR0IzOQ7vIMvkeOFWWQRIvZx3eA2bHJNbMWv3jgBfILc5Ip5ll99Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2136b8e667e46c62a16fb854b024cb7e2fb1128369e16bb6c987cc78719d772","last_reissued_at":"2026-05-18T00:25:28.892344Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:28.892344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.07888","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:25:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i6/Eei0hv9k/eZ38Q3trtXP5dPu5asrjd3IzWDjvqqlhchJ47m1HXBzp9CHS3IzgMibZ9dOK/K/EbsdghvifCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:21:33.405435Z"},"content_sha256":"8abb4cbefd8a156c907baf3b111f6b3bc81deda783e5b805be87484cd1660fce","schema_version":"1.0","event_id":"sha256:8abb4cbefd8a156c907baf3b111f6b3bc81deda783e5b805be87484cd1660fce"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:YIJWXDTGPZDMMKQW7OCUWASMW7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Mark Fuge, Wei Chen","submitted_at":"2017-08-25T21:12:40Z","abstract_excerpt":"Many engineering problems require identifying feasible domains under implicit constraints. One example is finding acceptable car body styling designs based on constraints like aesthetics and functionality. Current active-learning based methods learn feasible domains for bounded input spaces. However, we usually lack prior knowledge about how to set those input variable bounds. Bounds that are too small will fail to cover all feasible domains; while bounds that are too large will waste query budget. To avoid this problem, we introduce Active Expansion Sampling (AES), a method that identifies (p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.07888","kind":"arxiv","version":3},"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":"2026-05-18T00:25:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GWuFZTUokF5HzAjxVmubZUlq6jInkPaLSNWX6b75QHURQISTbUw0l5fjPxBMjBRvABsrMnloAVl+oTwx7GG5Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:21:33.405807Z"},"content_sha256":"7a29cb9c1b71c37aa6bdcc7dd5ec5508567b2536bafb47b70a72a8c7660ae338","schema_version":"1.0","event_id":"sha256:7a29cb9c1b71c37aa6bdcc7dd5ec5508567b2536bafb47b70a72a8c7660ae338"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YIJWXDTGPZDMMKQW7OCUWASMW7/bundle.json","state_url":"https://pith.science/pith/YIJWXDTGPZDMMKQW7OCUWASMW7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YIJWXDTGPZDMMKQW7OCUWASMW7/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":"2026-05-27T00:21:33Z","links":{"resolver":"https://pith.science/pith/YIJWXDTGPZDMMKQW7OCUWASMW7","bundle":"https://pith.science/pith/YIJWXDTGPZDMMKQW7OCUWASMW7/bundle.json","state":"https://pith.science/pith/YIJWXDTGPZDMMKQW7OCUWASMW7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YIJWXDTGPZDMMKQW7OCUWASMW7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:YIJWXDTGPZDMMKQW7OCUWASMW7","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":"be995229f33193b3f1caba2abcfe8ce164e1a10fd7028d4e0ade9ef41a3a822b","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-25T21:12:40Z","title_canon_sha256":"2333bf0f8e29f761f0a4bf90a3fef25532ef610ba221b23bc80586f3aac47643"},"schema_version":"1.0","source":{"id":"1708.07888","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.07888","created_at":"2026-05-18T00:25:28Z"},{"alias_kind":"arxiv_version","alias_value":"1708.07888v3","created_at":"2026-05-18T00:25:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.07888","created_at":"2026-05-18T00:25:28Z"},{"alias_kind":"pith_short_12","alias_value":"YIJWXDTGPZDM","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YIJWXDTGPZDMMKQW","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YIJWXDTG","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:7a29cb9c1b71c37aa6bdcc7dd5ec5508567b2536bafb47b70a72a8c7660ae338","target":"graph","created_at":"2026-05-18T00:25:28Z","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":"Many engineering problems require identifying feasible domains under implicit constraints. One example is finding acceptable car body styling designs based on constraints like aesthetics and functionality. Current active-learning based methods learn feasible domains for bounded input spaces. However, we usually lack prior knowledge about how to set those input variable bounds. Bounds that are too small will fail to cover all feasible domains; while bounds that are too large will waste query budget. To avoid this problem, we introduce Active Expansion Sampling (AES), a method that identifies (p","authors_text":"Mark Fuge, Wei Chen","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-25T21:12:40Z","title":"Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.07888","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":"sha256:8abb4cbefd8a156c907baf3b111f6b3bc81deda783e5b805be87484cd1660fce","target":"record","created_at":"2026-05-18T00:25:28Z","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":"be995229f33193b3f1caba2abcfe8ce164e1a10fd7028d4e0ade9ef41a3a822b","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-25T21:12:40Z","title_canon_sha256":"2333bf0f8e29f761f0a4bf90a3fef25532ef610ba221b23bc80586f3aac47643"},"schema_version":"1.0","source":{"id":"1708.07888","kind":"arxiv","version":3}},"canonical_sha256":"c2136b8e667e46c62a16fb854b024cb7e2fb1128369e16bb6c987cc78719d772","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c2136b8e667e46c62a16fb854b024cb7e2fb1128369e16bb6c987cc78719d772","first_computed_at":"2026-05-18T00:25:28.892344Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:25:28.892344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VhqX+z54Ve6ig48TPsBv1mkKxarM7Y3QjR0IzOQ7vIMvkeOFWWQRIvZx3eA2bHJNbMWv3jgBfILc5Ip5ll99Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:25:28.893131Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.07888","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8abb4cbefd8a156c907baf3b111f6b3bc81deda783e5b805be87484cd1660fce","sha256:7a29cb9c1b71c37aa6bdcc7dd5ec5508567b2536bafb47b70a72a8c7660ae338"],"state_sha256":"b4d679b9f05a6b937240eaeaccee6ea68d4b4d563b7362318f6c412b9789d768"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZoHEoMvpAS+eXtgleM4kTEMsllaKkoIh7nOIIlpzzQNv5bF3aoCWYrSurXuTGqmGcqW1V31IQoYXRIPYc3qnAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T00:21:33.409186Z","bundle_sha256":"c8763b850f498d83667737c32cf2fbbe848a3b8b754a7b36d5df30cda1968702"}}