{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:C5TYPSHTA5E3QZB25EFXFP4NUT","short_pith_number":"pith:C5TYPSHT","canonical_record":{"source":{"id":"2405.19539","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-05-29T21:53:24Z","cross_cats_sorted":[],"title_canon_sha256":"64c5022a108335da4a0b23a30f681ac919898f98e37c021802196ebaa41bc145","abstract_canon_sha256":"6520682ce60ccd79e0ff33be6afd255029439ca44ff9dfadb6a3e36c9c71976a"},"schema_version":"1.0"},"canonical_sha256":"176787c8f30749b8643ae90b72bf8da4db030971dd72240cb19ccf54b77cf156","source":{"kind":"arxiv","id":"2405.19539","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.19539","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"arxiv_version","alias_value":"2405.19539v1","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19539","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"pith_short_12","alias_value":"C5TYPSHTA5E3","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"pith_short_16","alias_value":"C5TYPSHTA5E3QZB2","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"pith_short_8","alias_value":"C5TYPSHT","created_at":"2026-07-05T08:25:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:C5TYPSHTA5E3QZB25EFXFP4NUT","target":"record","payload":{"canonical_record":{"source":{"id":"2405.19539","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-05-29T21:53:24Z","cross_cats_sorted":[],"title_canon_sha256":"64c5022a108335da4a0b23a30f681ac919898f98e37c021802196ebaa41bc145","abstract_canon_sha256":"6520682ce60ccd79e0ff33be6afd255029439ca44ff9dfadb6a3e36c9c71976a"},"schema_version":"1.0"},"canonical_sha256":"176787c8f30749b8643ae90b72bf8da4db030971dd72240cb19ccf54b77cf156","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:25:09.025460Z","signature_b64":"9kdnVE2h+LF6oTSOjknc5npm1atG2bT/4LDefMuXoo2TJKaNKoDOzIC42ge0EaNv4/XTBV7A87nQPVkw0utNCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"176787c8f30749b8643ae90b72bf8da4db030971dd72240cb19ccf54b77cf156","last_reissued_at":"2026-07-05T08:25:09.025029Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:25:09.025029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.19539","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":"2026-07-05T08:25:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n53nmn3PcrvBaiHmEHl5r8S7MgrGiL5xMzCEf9pHUJEqr9Gg66xGc5aS61OcIv1YBBAZtkhDERrrMqltC1jeDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T09:03:31.935151Z"},"content_sha256":"b45d6909e74288f66ddd319f00904bba1b80c8a16565fa276273a7a0be8cfe65","schema_version":"1.0","event_id":"sha256:b45d6909e74288f66ddd319f00904bba1b80c8a16565fa276273a7a0be8cfe65"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:C5TYPSHTA5E3QZB25EFXFP4NUT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Canonical Correlation Analysis as Reduced Rank Regression in High Dimensions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Claire Donnat, Elena Tuzhilina","submitted_at":"2024-05-29T21:53:24Z","abstract_excerpt":"Canonical Correlation Analysis (CCA) is a widespread technique for discovering linear relationships between two sets of variables $X \\in \\mathbb{R}^{n \\times p}$ and $Y \\in \\mathbb{R}^{n \\times q}$. In high dimensions however, standard estimates of the canonical directions cease to be consistent without assuming further structure. In this setting, a possible solution consists in leveraging the presumed sparsity of the solution: only a subset of the covariates span the canonical directions. While the last decade has seen a proliferation of sparse CCA methods, practical challenges regarding the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19539","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/2405.19539/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":"2026-07-05T08:25:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tZE0FM69nLJA2ZtkzbRij02m3ZHPi1ZfMqBsJNEqlfgodEJ6/YqwJeN9tsjoByUR2BV++q2dtG2s2HRhsWjDCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T09:03:31.935493Z"},"content_sha256":"edf3899546fa77aeed14afcde2b03e61d32c943eb479a721e31c3f7a2807acea","schema_version":"1.0","event_id":"sha256:edf3899546fa77aeed14afcde2b03e61d32c943eb479a721e31c3f7a2807acea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C5TYPSHTA5E3QZB25EFXFP4NUT/bundle.json","state_url":"https://pith.science/pith/C5TYPSHTA5E3QZB25EFXFP4NUT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C5TYPSHTA5E3QZB25EFXFP4NUT/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":"2026-08-14T09:03:31Z","links":{"resolver":"https://pith.science/pith/C5TYPSHTA5E3QZB25EFXFP4NUT","bundle":"https://pith.science/pith/C5TYPSHTA5E3QZB25EFXFP4NUT/bundle.json","state":"https://pith.science/pith/C5TYPSHTA5E3QZB25EFXFP4NUT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C5TYPSHTA5E3QZB25EFXFP4NUT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:C5TYPSHTA5E3QZB25EFXFP4NUT","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":"6520682ce60ccd79e0ff33be6afd255029439ca44ff9dfadb6a3e36c9c71976a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-05-29T21:53:24Z","title_canon_sha256":"64c5022a108335da4a0b23a30f681ac919898f98e37c021802196ebaa41bc145"},"schema_version":"1.0","source":{"id":"2405.19539","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.19539","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"arxiv_version","alias_value":"2405.19539v1","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19539","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"pith_short_12","alias_value":"C5TYPSHTA5E3","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"pith_short_16","alias_value":"C5TYPSHTA5E3QZB2","created_at":"2026-07-05T08:25:09Z"},{"alias_kind":"pith_short_8","alias_value":"C5TYPSHT","created_at":"2026-07-05T08:25:09Z"}],"graph_snapshots":[{"event_id":"sha256:edf3899546fa77aeed14afcde2b03e61d32c943eb479a721e31c3f7a2807acea","target":"graph","created_at":"2026-07-05T08:25:09Z","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/2405.19539/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Canonical Correlation Analysis (CCA) is a widespread technique for discovering linear relationships between two sets of variables $X \\in \\mathbb{R}^{n \\times p}$ and $Y \\in \\mathbb{R}^{n \\times q}$. In high dimensions however, standard estimates of the canonical directions cease to be consistent without assuming further structure. In this setting, a possible solution consists in leveraging the presumed sparsity of the solution: only a subset of the covariates span the canonical directions. While the last decade has seen a proliferation of sparse CCA methods, practical challenges regarding the ","authors_text":"Claire Donnat, Elena Tuzhilina","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-05-29T21:53:24Z","title":"Canonical Correlation Analysis as Reduced Rank Regression in High Dimensions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19539","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:b45d6909e74288f66ddd319f00904bba1b80c8a16565fa276273a7a0be8cfe65","target":"record","created_at":"2026-07-05T08:25:09Z","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":"6520682ce60ccd79e0ff33be6afd255029439ca44ff9dfadb6a3e36c9c71976a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-05-29T21:53:24Z","title_canon_sha256":"64c5022a108335da4a0b23a30f681ac919898f98e37c021802196ebaa41bc145"},"schema_version":"1.0","source":{"id":"2405.19539","kind":"arxiv","version":1}},"canonical_sha256":"176787c8f30749b8643ae90b72bf8da4db030971dd72240cb19ccf54b77cf156","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"176787c8f30749b8643ae90b72bf8da4db030971dd72240cb19ccf54b77cf156","first_computed_at":"2026-07-05T08:25:09.025029Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:25:09.025029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9kdnVE2h+LF6oTSOjknc5npm1atG2bT/4LDefMuXoo2TJKaNKoDOzIC42ge0EaNv4/XTBV7A87nQPVkw0utNCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:25:09.025460Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.19539","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b45d6909e74288f66ddd319f00904bba1b80c8a16565fa276273a7a0be8cfe65","sha256:edf3899546fa77aeed14afcde2b03e61d32c943eb479a721e31c3f7a2807acea"],"state_sha256":"a53a1a0ffef23511356115e09ed7a51a2540d4cdf0c41492afb0640b307b8542"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jEh9+fA5lppVq9cyyHuOX1mzlOVj5csN1I1WoQCqdYajiq7PSH40b0R5qodz2HO9PLvTwjXoiBVqgm9wp+52AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T09:03:31.938284Z","bundle_sha256":"8b8fc70e30df15e1ca8f5808df427e04ee94f85d944c991cfb2469569be0ad0a"}}