{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:OKJOF5ZPAJKB7MAQTAQPE2AYFL","short_pith_number":"pith:OKJOF5ZP","canonical_record":{"source":{"id":"2501.18975","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-31T09:11:06Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"060471ddb2406589a68f511cb31bbe985486990cd48b3adf9e570d88c57fd091","abstract_canon_sha256":"4c4674308f0857d4e788fb26d25c56032e2c86613403239a265fdb8c84ba1764"},"schema_version":"1.0"},"canonical_sha256":"7292e2f72f02541fb0109820f268182ad3329f08d2a17b4c77a69ff909288eeb","source":{"kind":"arxiv","id":"2501.18975","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.18975","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"arxiv_version","alias_value":"2501.18975v2","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.18975","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"pith_short_12","alias_value":"OKJOF5ZPAJKB","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"pith_short_16","alias_value":"OKJOF5ZPAJKB7MAQ","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"pith_short_8","alias_value":"OKJOF5ZP","created_at":"2026-07-05T10:13:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:OKJOF5ZPAJKB7MAQTAQPE2AYFL","target":"record","payload":{"canonical_record":{"source":{"id":"2501.18975","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-31T09:11:06Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"060471ddb2406589a68f511cb31bbe985486990cd48b3adf9e570d88c57fd091","abstract_canon_sha256":"4c4674308f0857d4e788fb26d25c56032e2c86613403239a265fdb8c84ba1764"},"schema_version":"1.0"},"canonical_sha256":"7292e2f72f02541fb0109820f268182ad3329f08d2a17b4c77a69ff909288eeb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:13:47.122950Z","signature_b64":"8/sqnAAyGzORiTxwI7zfpbNscJ44vMkWtRi+7HftPgo2uH2uNodUIcT6BkF6iTGmVhPILa9l0KfeMb/7CHDUBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7292e2f72f02541fb0109820f268182ad3329f08d2a17b4c77a69ff909288eeb","last_reissued_at":"2026-07-05T10:13:47.118764Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:13:47.118764Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.18975","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:13:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j/tYIIHA+0PlXEkOdLtCkd/E7v3gqtBJScJwNpd86aOlacriJEiCABu5GyRPp1OjpEayoV5Y0LoNZhL5I7oFBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T03:30:32.730557Z"},"content_sha256":"a8ef6d1fe6243202b0e45fb475fe284c0dcc9110a97275eed0097fe7ed2f64be","schema_version":"1.0","event_id":"sha256:a8ef6d1fe6243202b0e45fb475fe284c0dcc9110a97275eed0097fe7ed2f64be"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:OKJOF5ZPAJKB7MAQTAQPE2AYFL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Meta-learning of shared linear representations beyond well-specified linear regression","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Laurent Massouli\\'e, Mathieu Even","submitted_at":"2025-01-31T09:11:06Z","abstract_excerpt":"Motivated by multi-task and meta-learning approaches, we consider the problem of learning structure shared by tasks or users, such as shared low-rank representations or clustered structures. While all previous works focus on well-specified linear regression, we consider more general convex objectives, where the structural low-rank and cluster assumptions are expressed on the optima of each function. We show that under mild assumptions such as \\textit{Hessian concentration} and \\textit{noise concentration at the optimum}, rank and clustered regularized estimators recover such structure, provide"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.18975","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/2501.18975/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":"2026-07-05T10:13:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"keO+PuT1JB75A6176F2xukgYTynx5Vc0CYoZDrsv1tQWXzOEk5UyiMWe8aRHc6HIyyHfcnVD0OGOeEjDs0+UAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T03:30:32.730950Z"},"content_sha256":"fc3a35c67d65a047c0037b9e240269bf248e6d38bf9b988b6157b219fa3b27c4","schema_version":"1.0","event_id":"sha256:fc3a35c67d65a047c0037b9e240269bf248e6d38bf9b988b6157b219fa3b27c4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OKJOF5ZPAJKB7MAQTAQPE2AYFL/bundle.json","state_url":"https://pith.science/pith/OKJOF5ZPAJKB7MAQTAQPE2AYFL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OKJOF5ZPAJKB7MAQTAQPE2AYFL/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":"2026-08-11T03:30:32Z","links":{"resolver":"https://pith.science/pith/OKJOF5ZPAJKB7MAQTAQPE2AYFL","bundle":"https://pith.science/pith/OKJOF5ZPAJKB7MAQTAQPE2AYFL/bundle.json","state":"https://pith.science/pith/OKJOF5ZPAJKB7MAQTAQPE2AYFL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OKJOF5ZPAJKB7MAQTAQPE2AYFL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:OKJOF5ZPAJKB7MAQTAQPE2AYFL","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":"4c4674308f0857d4e788fb26d25c56032e2c86613403239a265fdb8c84ba1764","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-31T09:11:06Z","title_canon_sha256":"060471ddb2406589a68f511cb31bbe985486990cd48b3adf9e570d88c57fd091"},"schema_version":"1.0","source":{"id":"2501.18975","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.18975","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"arxiv_version","alias_value":"2501.18975v2","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.18975","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"pith_short_12","alias_value":"OKJOF5ZPAJKB","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"pith_short_16","alias_value":"OKJOF5ZPAJKB7MAQ","created_at":"2026-07-05T10:13:47Z"},{"alias_kind":"pith_short_8","alias_value":"OKJOF5ZP","created_at":"2026-07-05T10:13:47Z"}],"graph_snapshots":[{"event_id":"sha256:fc3a35c67d65a047c0037b9e240269bf248e6d38bf9b988b6157b219fa3b27c4","target":"graph","created_at":"2026-07-05T10:13:47Z","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/2501.18975/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Motivated by multi-task and meta-learning approaches, we consider the problem of learning structure shared by tasks or users, such as shared low-rank representations or clustered structures. While all previous works focus on well-specified linear regression, we consider more general convex objectives, where the structural low-rank and cluster assumptions are expressed on the optima of each function. We show that under mild assumptions such as \\textit{Hessian concentration} and \\textit{noise concentration at the optimum}, rank and clustered regularized estimators recover such structure, provide","authors_text":"Laurent Massouli\\'e, Mathieu Even","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-31T09:11:06Z","title":"Meta-learning of shared linear representations beyond well-specified linear regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.18975","kind":"arxiv","version":2},"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:a8ef6d1fe6243202b0e45fb475fe284c0dcc9110a97275eed0097fe7ed2f64be","target":"record","created_at":"2026-07-05T10:13:47Z","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":"4c4674308f0857d4e788fb26d25c56032e2c86613403239a265fdb8c84ba1764","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-31T09:11:06Z","title_canon_sha256":"060471ddb2406589a68f511cb31bbe985486990cd48b3adf9e570d88c57fd091"},"schema_version":"1.0","source":{"id":"2501.18975","kind":"arxiv","version":2}},"canonical_sha256":"7292e2f72f02541fb0109820f268182ad3329f08d2a17b4c77a69ff909288eeb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7292e2f72f02541fb0109820f268182ad3329f08d2a17b4c77a69ff909288eeb","first_computed_at":"2026-07-05T10:13:47.118764Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:13:47.118764Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8/sqnAAyGzORiTxwI7zfpbNscJ44vMkWtRi+7HftPgo2uH2uNodUIcT6BkF6iTGmVhPILa9l0KfeMb/7CHDUBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:13:47.122950Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.18975","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8ef6d1fe6243202b0e45fb475fe284c0dcc9110a97275eed0097fe7ed2f64be","sha256:fc3a35c67d65a047c0037b9e240269bf248e6d38bf9b988b6157b219fa3b27c4"],"state_sha256":"4cd053f474502d75c941f848d378ed5500bee116048d7cce32eb06eee9c291dd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"skKhgJGTQfX7FOy0ohW1E5KFDdWq/1+opZVQqIjOD+tCxTevE2UZA8E0VgetMksOKNBo85tn5YyD7DbOAzsGAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T03:30:32.733670Z","bundle_sha256":"d719e66c4dc8791a2e5d5977da490de224ab40d379701f6348f5091c0590c8fa"}}