{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:3IUDVFNOMC4ZJ2HW2PER3LAPJL","short_pith_number":"pith:3IUDVFNO","canonical_record":{"source":{"id":"1803.10309","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-27T20:36:26Z","cross_cats_sorted":["cs.SY","stat.ML"],"title_canon_sha256":"be7989b8eaf70b66e8b823b9008062607364603cdd52f63833053b978ddbbbff","abstract_canon_sha256":"515140d0a1cabb9fc0bb5700fbb8547d75dc471409734cddc8ab708552f767f3"},"schema_version":"1.0"},"canonical_sha256":"da283a95ae60b994e8f6d3c91dac0f4afed57a5ce1e7686af25ff1dd476992b1","source":{"kind":"arxiv","id":"1803.10309","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.10309","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"1803.10309v1","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.10309","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"3IUDVFNOMC4Z","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3IUDVFNOMC4ZJ2HW","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3IUDVFNO","created_at":"2026-05-18T12:32:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:3IUDVFNOMC4ZJ2HW2PER3LAPJL","target":"record","payload":{"canonical_record":{"source":{"id":"1803.10309","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-27T20:36:26Z","cross_cats_sorted":["cs.SY","stat.ML"],"title_canon_sha256":"be7989b8eaf70b66e8b823b9008062607364603cdd52f63833053b978ddbbbff","abstract_canon_sha256":"515140d0a1cabb9fc0bb5700fbb8547d75dc471409734cddc8ab708552f767f3"},"schema_version":"1.0"},"canonical_sha256":"da283a95ae60b994e8f6d3c91dac0f4afed57a5ce1e7686af25ff1dd476992b1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:15.151280Z","signature_b64":"SNhSiJW/CJD+J4KvSbEpsYFmTJ1kr9tQ7mTghBvkoYVitENy332bJtBK1mbcTiQ9XJnhKTI44ZSB/Ht4YBNDDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"da283a95ae60b994e8f6d3c91dac0f4afed57a5ce1e7686af25ff1dd476992b1","last_reissued_at":"2026-05-18T00:08:15.150864Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:15.150864Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.10309","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":"2026-05-18T00:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tzivsWaR4Gm8fq9Hnm5IYQT9OlC7bpHWW6g320QJmo+25Yx6jtNYCYksTx4g6xmyq5+5aP+Kcvo6MHGn7kRsDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T20:45:23.129489Z"},"content_sha256":"7a3b713addb7369ad8a2fdb452a536db7f3c0a68c6633799259b4597a55bcf75","schema_version":"1.0","event_id":"sha256:7a3b713addb7369ad8a2fdb452a536db7f3c0a68c6633799259b4597a55bcf75"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:3IUDVFNOMC4ZJ2HW2PER3LAPJL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Canonical Correlation Analysis of Datasets with a Common Source Graph","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","stat.ML"],"primary_cat":"cs.LG","authors_text":"Gang Wang, Georgios B. Giannakis, Jia Chen, Yanning Shen","submitted_at":"2018-03-27T20:36:26Z","abstract_excerpt":"Canonical correlation analysis (CCA) is a powerful technique for discovering whether or not hidden sources are commonly present in two (or more) datasets. Its well-appreciated merits include dimensionality reduction, clustering, classification, feature selection, and data fusion. The standard CCA however, does not exploit the geometry of the common sources, which may be available from the given data or can be deduced from (cross-) correlations. In this paper, this extra information provided by the common sources generating the data is encoded in a graph, and is invoked as a graph regularizer. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.10309","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":"2026-05-18T00:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NDEUM5ztOvBAQtVupwQ+pmcos8gztuM2f5W7Yyc0+c5WoiXP27Xl5jxHlANUoJcdC7EX/drvBfVV8eeiljtbCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T20:45:23.129837Z"},"content_sha256":"17a279a1c13783a43370fcf33a75fa9b6a5abf688bc3e32b83cb65226647977c","schema_version":"1.0","event_id":"sha256:17a279a1c13783a43370fcf33a75fa9b6a5abf688bc3e32b83cb65226647977c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3IUDVFNOMC4ZJ2HW2PER3LAPJL/bundle.json","state_url":"https://pith.science/pith/3IUDVFNOMC4ZJ2HW2PER3LAPJL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3IUDVFNOMC4ZJ2HW2PER3LAPJL/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":"2026-05-19T20:45:23Z","links":{"resolver":"https://pith.science/pith/3IUDVFNOMC4ZJ2HW2PER3LAPJL","bundle":"https://pith.science/pith/3IUDVFNOMC4ZJ2HW2PER3LAPJL/bundle.json","state":"https://pith.science/pith/3IUDVFNOMC4ZJ2HW2PER3LAPJL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3IUDVFNOMC4ZJ2HW2PER3LAPJL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:3IUDVFNOMC4ZJ2HW2PER3LAPJL","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":"515140d0a1cabb9fc0bb5700fbb8547d75dc471409734cddc8ab708552f767f3","cross_cats_sorted":["cs.SY","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-27T20:36:26Z","title_canon_sha256":"be7989b8eaf70b66e8b823b9008062607364603cdd52f63833053b978ddbbbff"},"schema_version":"1.0","source":{"id":"1803.10309","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.10309","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"1803.10309v1","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.10309","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"3IUDVFNOMC4Z","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3IUDVFNOMC4ZJ2HW","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3IUDVFNO","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:17a279a1c13783a43370fcf33a75fa9b6a5abf688bc3e32b83cb65226647977c","target":"graph","created_at":"2026-05-18T00:08:15Z","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":"Canonical correlation analysis (CCA) is a powerful technique for discovering whether or not hidden sources are commonly present in two (or more) datasets. Its well-appreciated merits include dimensionality reduction, clustering, classification, feature selection, and data fusion. The standard CCA however, does not exploit the geometry of the common sources, which may be available from the given data or can be deduced from (cross-) correlations. In this paper, this extra information provided by the common sources generating the data is encoded in a graph, and is invoked as a graph regularizer. ","authors_text":"Gang Wang, Georgios B. Giannakis, Jia Chen, Yanning Shen","cross_cats":["cs.SY","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-27T20:36:26Z","title":"Canonical Correlation Analysis of Datasets with a Common Source Graph"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.10309","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":"sha256:7a3b713addb7369ad8a2fdb452a536db7f3c0a68c6633799259b4597a55bcf75","target":"record","created_at":"2026-05-18T00:08:15Z","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":"515140d0a1cabb9fc0bb5700fbb8547d75dc471409734cddc8ab708552f767f3","cross_cats_sorted":["cs.SY","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-27T20:36:26Z","title_canon_sha256":"be7989b8eaf70b66e8b823b9008062607364603cdd52f63833053b978ddbbbff"},"schema_version":"1.0","source":{"id":"1803.10309","kind":"arxiv","version":1}},"canonical_sha256":"da283a95ae60b994e8f6d3c91dac0f4afed57a5ce1e7686af25ff1dd476992b1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"da283a95ae60b994e8f6d3c91dac0f4afed57a5ce1e7686af25ff1dd476992b1","first_computed_at":"2026-05-18T00:08:15.150864Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:08:15.150864Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SNhSiJW/CJD+J4KvSbEpsYFmTJ1kr9tQ7mTghBvkoYVitENy332bJtBK1mbcTiQ9XJnhKTI44ZSB/Ht4YBNDDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:08:15.151280Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.10309","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7a3b713addb7369ad8a2fdb452a536db7f3c0a68c6633799259b4597a55bcf75","sha256:17a279a1c13783a43370fcf33a75fa9b6a5abf688bc3e32b83cb65226647977c"],"state_sha256":"b4e67437659437e4919fd6b68677616e89b5b3e8d4efdcb9add3256159b654ab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6CrXV7ljf7HBdsPrC9ySDYFaM2rOQ7mnYBsC1iSJo/Dr6lp60EPOeENZJF/ZOLuPdzikhK1VB6A2n/Sga/QJCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-19T20:45:23.132128Z","bundle_sha256":"bc93f96eabd1c2756ee62f90dde84e5e50b67f438e44ebe16dec54f56a016ab5"}}