{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:LZRAWYNHJDFKJ35NSNCJ2G3VLO","short_pith_number":"pith:LZRAWYNH","canonical_record":{"source":{"id":"1712.00573","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T08:43:23Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"35829f88e78b385adb8de2825d32147de15f3a9d032432d15e141e5042250ede","abstract_canon_sha256":"ebdff9f64b505c95d38ec1300bc16cbd5000abd8467521bdc0c52fb94aed8e2f"},"schema_version":"1.0"},"canonical_sha256":"5e620b61a748caa4efad93449d1b755bb2ad5a3fe11bdf0d5b3c73aaacd3ddc7","source":{"kind":"arxiv","id":"1712.00573","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00573","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00573v1","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00573","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"pith_short_12","alias_value":"LZRAWYNHJDFK","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LZRAWYNHJDFKJ35N","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LZRAWYNH","created_at":"2026-05-18T12:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:LZRAWYNHJDFKJ35NSNCJ2G3VLO","target":"record","payload":{"canonical_record":{"source":{"id":"1712.00573","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T08:43:23Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"35829f88e78b385adb8de2825d32147de15f3a9d032432d15e141e5042250ede","abstract_canon_sha256":"ebdff9f64b505c95d38ec1300bc16cbd5000abd8467521bdc0c52fb94aed8e2f"},"schema_version":"1.0"},"canonical_sha256":"5e620b61a748caa4efad93449d1b755bb2ad5a3fe11bdf0d5b3c73aaacd3ddc7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:04.840068Z","signature_b64":"cleGEC1dpZbmbuRmFTJgt0Ic9MNdLa5hqo900WbuuzvbYu1t6e/RxcdxmIQY1FdhZLh5/pa7NxEMqEqCMkVjAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5e620b61a748caa4efad93449d1b755bb2ad5a3fe11bdf0d5b3c73aaacd3ddc7","last_reissued_at":"2026-05-18T00:29:04.839396Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:04.839396Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.00573","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":"2026-05-18T00:29:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yvUqGeAKLXBzQtmbORK5BdFI3pvqoOQPWysAccMdVLqFdqS8CfekJ2VHRS/43LTpkFCUtNfaPMOEPLN1xpYqDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T16:55:55.668759Z"},"content_sha256":"7c40ce15456dd0f5c5ab70f59985531cf70034afcde61a8ca59d1ca96fadbbdd","schema_version":"1.0","event_id":"sha256:7c40ce15456dd0f5c5ab70f59985531cf70034afcde61a8ca59d1ca96fadbbdd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:LZRAWYNHJDFKJ35NSNCJ2G3VLO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Supervised Hashing based on Energy Minimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Hongtao Lu, Xiyi Luo, Yong Yu, Zihao Hu","submitted_at":"2017-12-02T08:43:23Z","abstract_excerpt":"Recently, supervised hashing methods have attracted much attention since they can optimize retrieval speed and storage cost while preserving semantic information. Because hashing codes learning is NP-hard, many methods resort to some form of relaxation technique. But the performance of these methods can easily deteriorate due to the relaxation. Luckily, many supervised hashing formulations can be viewed as energy functions, hence solving hashing codes is equivalent to learning marginals in the corresponding conditional random field (CRF). By minimizing the KL divergence between a fully factori"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00573","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":"2026-05-18T00:29:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ApTdHEm04TQ1JcacHXwlSAupKC9ANRHLRdZ9nRIv+qIf4R89IIEOoSk3WazZ2iXeBuO42CPT35tx/fBEnQSpCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T16:55:55.669450Z"},"content_sha256":"c78a2333cadcd2cffd300ec75da2949d1dae426353af026f0461429dfc389c34","schema_version":"1.0","event_id":"sha256:c78a2333cadcd2cffd300ec75da2949d1dae426353af026f0461429dfc389c34"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LZRAWYNHJDFKJ35NSNCJ2G3VLO/bundle.json","state_url":"https://pith.science/pith/LZRAWYNHJDFKJ35NSNCJ2G3VLO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LZRAWYNHJDFKJ35NSNCJ2G3VLO/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":"2026-05-26T16:55:55Z","links":{"resolver":"https://pith.science/pith/LZRAWYNHJDFKJ35NSNCJ2G3VLO","bundle":"https://pith.science/pith/LZRAWYNHJDFKJ35NSNCJ2G3VLO/bundle.json","state":"https://pith.science/pith/LZRAWYNHJDFKJ35NSNCJ2G3VLO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LZRAWYNHJDFKJ35NSNCJ2G3VLO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LZRAWYNHJDFKJ35NSNCJ2G3VLO","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":"ebdff9f64b505c95d38ec1300bc16cbd5000abd8467521bdc0c52fb94aed8e2f","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T08:43:23Z","title_canon_sha256":"35829f88e78b385adb8de2825d32147de15f3a9d032432d15e141e5042250ede"},"schema_version":"1.0","source":{"id":"1712.00573","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00573","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00573v1","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00573","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"pith_short_12","alias_value":"LZRAWYNHJDFK","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LZRAWYNHJDFKJ35N","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LZRAWYNH","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:c78a2333cadcd2cffd300ec75da2949d1dae426353af026f0461429dfc389c34","target":"graph","created_at":"2026-05-18T00:29:04Z","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":"Recently, supervised hashing methods have attracted much attention since they can optimize retrieval speed and storage cost while preserving semantic information. Because hashing codes learning is NP-hard, many methods resort to some form of relaxation technique. But the performance of these methods can easily deteriorate due to the relaxation. Luckily, many supervised hashing formulations can be viewed as energy functions, hence solving hashing codes is equivalent to learning marginals in the corresponding conditional random field (CRF). By minimizing the KL divergence between a fully factori","authors_text":"Hongtao Lu, Xiyi Luo, Yong Yu, Zihao Hu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T08:43:23Z","title":"Supervised Hashing based on Energy Minimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00573","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":"sha256:7c40ce15456dd0f5c5ab70f59985531cf70034afcde61a8ca59d1ca96fadbbdd","target":"record","created_at":"2026-05-18T00:29:04Z","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":"ebdff9f64b505c95d38ec1300bc16cbd5000abd8467521bdc0c52fb94aed8e2f","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T08:43:23Z","title_canon_sha256":"35829f88e78b385adb8de2825d32147de15f3a9d032432d15e141e5042250ede"},"schema_version":"1.0","source":{"id":"1712.00573","kind":"arxiv","version":1}},"canonical_sha256":"5e620b61a748caa4efad93449d1b755bb2ad5a3fe11bdf0d5b3c73aaacd3ddc7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5e620b61a748caa4efad93449d1b755bb2ad5a3fe11bdf0d5b3c73aaacd3ddc7","first_computed_at":"2026-05-18T00:29:04.839396Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:04.839396Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cleGEC1dpZbmbuRmFTJgt0Ic9MNdLa5hqo900WbuuzvbYu1t6e/RxcdxmIQY1FdhZLh5/pa7NxEMqEqCMkVjAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:04.840068Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.00573","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c40ce15456dd0f5c5ab70f59985531cf70034afcde61a8ca59d1ca96fadbbdd","sha256:c78a2333cadcd2cffd300ec75da2949d1dae426353af026f0461429dfc389c34"],"state_sha256":"db3b1b8355ba17fb9aad12e631f9c590e9002e78743d1227e9491d571d940bbc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c0cmoIEZQYAD8h6vf7KpVQ473zRzPQrgsCL2JW710lcIULZtjdljrWi2OTlezuPYIy17B+y1l0TQalS+6EvCAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T16:55:55.672876Z","bundle_sha256":"df6fa3830ee5e93abbefa98c3c39cff77e6b356b0502f8b0c3951736b594b2c7"}}