{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:LRYHY2QJ57X6HN7JW4ZSFEDEU2","short_pith_number":"pith:LRYHY2QJ","schema_version":"1.0","canonical_sha256":"5c707c6a09efefe3b7e9b733229064a6b371abf6bf5752f98d94accd3e4cfe4b","source":{"kind":"arxiv","id":"2105.03396","version":2},"attestation_state":"computed","paper":{"title":"Double-matched matrix decomposition for multi-view data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.ME","authors_text":"Dongbang Yuan, Irina Gaynanova","submitted_at":"2021-05-07T17:09:57Z","abstract_excerpt":"We consider the problem of extracting joint and individual signals from multi-view data, that is data collected from different sources on matched samples. While existing methods for multi-view data decomposition explore single matching of data by samples, we focus on double-matched multi-view data (matched by both samples and source features). Our motivating example is the miRNA data collected from both primary tumor and normal tissues of the same subjects; the measurements from two tissues are thus matched both by subjects and by miRNAs. Our proposed double-matched matrix decomposition allows"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2105.03396","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2021-05-07T17:09:57Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"d53b2cefbc36081224653e5bbabf969fae3e6c9af8fa4b669c2dacfdcfe91e1b","abstract_canon_sha256":"fb259c797410d000792710f1f394ec5856f7d0a05ed76780c7e12abcb173f396"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:16:12.308256Z","signature_b64":"8hPAdbiC4AR9RY09s3csCkfGtYeXy6FCWQqEXGAxm5f4zDYxsEIn+XCJhCgnbZSS0XuNbdB/EpGdvcmQSmQrDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5c707c6a09efefe3b7e9b733229064a6b371abf6bf5752f98d94accd3e4cfe4b","last_reissued_at":"2026-07-05T04:16:12.307832Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:16:12.307832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Double-matched matrix decomposition for multi-view data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.ME","authors_text":"Dongbang Yuan, Irina Gaynanova","submitted_at":"2021-05-07T17:09:57Z","abstract_excerpt":"We consider the problem of extracting joint and individual signals from multi-view data, that is data collected from different sources on matched samples. While existing methods for multi-view data decomposition explore single matching of data by samples, we focus on double-matched multi-view data (matched by both samples and source features). Our motivating example is the miRNA data collected from both primary tumor and normal tissues of the same subjects; the measurements from two tissues are thus matched both by subjects and by miRNAs. Our proposed double-matched matrix decomposition allows"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.03396","kind":"arxiv","version":2},"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/2105.03396/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2105.03396","created_at":"2026-07-05T04:16:12.307889+00:00"},{"alias_kind":"arxiv_version","alias_value":"2105.03396v2","created_at":"2026-07-05T04:16:12.307889+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.03396","created_at":"2026-07-05T04:16:12.307889+00:00"},{"alias_kind":"pith_short_12","alias_value":"LRYHY2QJ57X6","created_at":"2026-07-05T04:16:12.307889+00:00"},{"alias_kind":"pith_short_16","alias_value":"LRYHY2QJ57X6HN7J","created_at":"2026-07-05T04:16:12.307889+00:00"},{"alias_kind":"pith_short_8","alias_value":"LRYHY2QJ","created_at":"2026-07-05T04:16:12.307889+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2","json":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2.json","graph_json":"https://pith.science/api/pith-number/LRYHY2QJ57X6HN7JW4ZSFEDEU2/graph.json","events_json":"https://pith.science/api/pith-number/LRYHY2QJ57X6HN7JW4ZSFEDEU2/events.json","paper":"https://pith.science/paper/LRYHY2QJ"},"agent_actions":{"view_html":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2","download_json":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2.json","view_paper":"https://pith.science/paper/LRYHY2QJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2105.03396&json=true","fetch_graph":"https://pith.science/api/pith-number/LRYHY2QJ57X6HN7JW4ZSFEDEU2/graph.json","fetch_events":"https://pith.science/api/pith-number/LRYHY2QJ57X6HN7JW4ZSFEDEU2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2/action/storage_attestation","attest_author":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2/action/author_attestation","sign_citation":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2/action/citation_signature","submit_replication":"https://pith.science/pith/LRYHY2QJ57X6HN7JW4ZSFEDEU2/action/replication_record"}},"created_at":"2026-07-05T04:16:12.307889+00:00","updated_at":"2026-07-05T04:16:12.307889+00:00"}