{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:G4M3QHWP4Y7XBQVJOWYGOGBXIT","short_pith_number":"pith:G4M3QHWP","canonical_record":{"source":{"id":"2503.00174","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T20:40:00Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e28ba3d14fa1daa7843c8afdfa2b102e0ccd152f1aec905a5f63ec3e623efcc6","abstract_canon_sha256":"5c10c4c058500c4923e4da29019e4381ffd8f0ed8e6452c4085698391e0dde7f"},"schema_version":"1.0"},"canonical_sha256":"3719b81ecfe63f70c2a975b067183744d30c28e4f7fea4022cf490bd50945560","source":{"kind":"arxiv","id":"2503.00174","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.00174","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"arxiv_version","alias_value":"2503.00174v1","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.00174","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"pith_short_12","alias_value":"G4M3QHWP4Y7X","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"pith_short_16","alias_value":"G4M3QHWP4Y7XBQVJ","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"pith_short_8","alias_value":"G4M3QHWP","created_at":"2026-07-05T10:22:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:G4M3QHWP4Y7XBQVJOWYGOGBXIT","target":"record","payload":{"canonical_record":{"source":{"id":"2503.00174","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T20:40:00Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e28ba3d14fa1daa7843c8afdfa2b102e0ccd152f1aec905a5f63ec3e623efcc6","abstract_canon_sha256":"5c10c4c058500c4923e4da29019e4381ffd8f0ed8e6452c4085698391e0dde7f"},"schema_version":"1.0"},"canonical_sha256":"3719b81ecfe63f70c2a975b067183744d30c28e4f7fea4022cf490bd50945560","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:22:18.569047Z","signature_b64":"9KDeO1V7aIlnCJYKrLj4A6oHBqQ+fUKu/b98uozhgDOVIf2BiDZgbtUa5U9G8jpUbM36RUAtiFdn251GllckCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3719b81ecfe63f70c2a975b067183744d30c28e4f7fea4022cf490bd50945560","last_reissued_at":"2026-07-05T10:22:18.568553Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:22:18.568553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.00174","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":"2026-07-05T10:22:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ArhFJLekWufdYjYmyLWgRPezKc6oVmTyQSZvopAx3B1vDb3oIEH8dw0lziiPryW8PBZqCjJ1ACMdfbIh8k/EAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T09:08:42.423271Z"},"content_sha256":"1d01d8f52100b60a780018203b4d3b8e7b40db64802dc7dc3a1873bd5e565849","schema_version":"1.0","event_id":"sha256:1d01d8f52100b60a780018203b4d3b8e7b40db64802dc7dc3a1873bd5e565849"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:G4M3QHWP4Y7XBQVJOWYGOGBXIT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimal Transfer Learning for Missing Not-at-Random Matrix Completion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Akhil Jalan, Arya Mazumdar, Purnamrita Sarkar, Soumendu Sundar Mukherjee, Yassir Jedra","submitted_at":"2025-02-28T20:40:00Z","abstract_excerpt":"We study transfer learning for matrix completion in a Missing Not-at-Random (MNAR) setting that is motivated by biological problems. The target matrix $Q$ has entire rows and columns missing, making estimation impossible without side information. To address this, we use a noisy and incomplete source matrix $P$, which relates to $Q$ via a feature shift in latent space. We consider both the active and passive sampling of rows and columns. We establish minimax lower bounds for entrywise estimation error in each setting. Our computationally efficient estimation framework achieves this lower bound "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.00174","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/2503.00174/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":"2026-07-05T10:22:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8JwsRj0L6US+cMfXlJl4xId5XGcIHSXFYtfljPN1YSZkIbo3007IirL8MRGxgtNbmQxBgy/Xy/YqUm4sjwYLAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T09:08:42.423987Z"},"content_sha256":"b3a270e2598a1bf0b67dbc5f914bd433e72af30f93c3c7e41db41927b2afa54e","schema_version":"1.0","event_id":"sha256:b3a270e2598a1bf0b67dbc5f914bd433e72af30f93c3c7e41db41927b2afa54e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G4M3QHWP4Y7XBQVJOWYGOGBXIT/bundle.json","state_url":"https://pith.science/pith/G4M3QHWP4Y7XBQVJOWYGOGBXIT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G4M3QHWP4Y7XBQVJOWYGOGBXIT/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":"2026-08-21T09:08:42Z","links":{"resolver":"https://pith.science/pith/G4M3QHWP4Y7XBQVJOWYGOGBXIT","bundle":"https://pith.science/pith/G4M3QHWP4Y7XBQVJOWYGOGBXIT/bundle.json","state":"https://pith.science/pith/G4M3QHWP4Y7XBQVJOWYGOGBXIT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G4M3QHWP4Y7XBQVJOWYGOGBXIT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:G4M3QHWP4Y7XBQVJOWYGOGBXIT","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":"5c10c4c058500c4923e4da29019e4381ffd8f0ed8e6452c4085698391e0dde7f","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T20:40:00Z","title_canon_sha256":"e28ba3d14fa1daa7843c8afdfa2b102e0ccd152f1aec905a5f63ec3e623efcc6"},"schema_version":"1.0","source":{"id":"2503.00174","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.00174","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"arxiv_version","alias_value":"2503.00174v1","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.00174","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"pith_short_12","alias_value":"G4M3QHWP4Y7X","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"pith_short_16","alias_value":"G4M3QHWP4Y7XBQVJ","created_at":"2026-07-05T10:22:18Z"},{"alias_kind":"pith_short_8","alias_value":"G4M3QHWP","created_at":"2026-07-05T10:22:18Z"}],"graph_snapshots":[{"event_id":"sha256:b3a270e2598a1bf0b67dbc5f914bd433e72af30f93c3c7e41db41927b2afa54e","target":"graph","created_at":"2026-07-05T10:22:18Z","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/2503.00174/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study transfer learning for matrix completion in a Missing Not-at-Random (MNAR) setting that is motivated by biological problems. The target matrix $Q$ has entire rows and columns missing, making estimation impossible without side information. To address this, we use a noisy and incomplete source matrix $P$, which relates to $Q$ via a feature shift in latent space. We consider both the active and passive sampling of rows and columns. We establish minimax lower bounds for entrywise estimation error in each setting. Our computationally efficient estimation framework achieves this lower bound ","authors_text":"Akhil Jalan, Arya Mazumdar, Purnamrita Sarkar, Soumendu Sundar Mukherjee, Yassir Jedra","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T20:40:00Z","title":"Optimal Transfer Learning for Missing Not-at-Random Matrix Completion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.00174","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":"sha256:1d01d8f52100b60a780018203b4d3b8e7b40db64802dc7dc3a1873bd5e565849","target":"record","created_at":"2026-07-05T10:22:18Z","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":"5c10c4c058500c4923e4da29019e4381ffd8f0ed8e6452c4085698391e0dde7f","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T20:40:00Z","title_canon_sha256":"e28ba3d14fa1daa7843c8afdfa2b102e0ccd152f1aec905a5f63ec3e623efcc6"},"schema_version":"1.0","source":{"id":"2503.00174","kind":"arxiv","version":1}},"canonical_sha256":"3719b81ecfe63f70c2a975b067183744d30c28e4f7fea4022cf490bd50945560","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3719b81ecfe63f70c2a975b067183744d30c28e4f7fea4022cf490bd50945560","first_computed_at":"2026-07-05T10:22:18.568553Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:22:18.568553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9KDeO1V7aIlnCJYKrLj4A6oHBqQ+fUKu/b98uozhgDOVIf2BiDZgbtUa5U9G8jpUbM36RUAtiFdn251GllckCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:22:18.569047Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.00174","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1d01d8f52100b60a780018203b4d3b8e7b40db64802dc7dc3a1873bd5e565849","sha256:b3a270e2598a1bf0b67dbc5f914bd433e72af30f93c3c7e41db41927b2afa54e"],"state_sha256":"53ea20b054ea49ec77560af42d5b331e21469f584fe7f9c6714ca7d7e4bd0ec5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ge28B89tv6Oucv3EOdrz23KcNNeRtmSTkSlyc+hMk2tZTjOrJI6iE8smO6eLHYo3QZDY4eMvuVTrPAMLlH6LDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T09:08:42.437116Z","bundle_sha256":"7cce744862c190947f6a100896cf6b808c7dc1c00e0806ed97cfc487cefd1b51"}}