{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:A7M4BU6KVFP5L6ORQKGM74COON","short_pith_number":"pith:A7M4BU6K","schema_version":"1.0","canonical_sha256":"07d9c0d3caa95fd5f9d1828ccff04e737b3d106d24aca1b790575f0ccfeef5b9","source":{"kind":"arxiv","id":"1610.07488","version":2},"attestation_state":"computed","paper":{"title":"Laplacian regularized low rank subspace clustering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Yiquan Wu, Yu Song","submitted_at":"2016-10-24T16:51:05Z","abstract_excerpt":"The problem of fitting a union of subspaces to a collection of data points drawn from multiple subspaces is considered in this paper. In the traditional low rank representation model, the dictionary used to represent the data points is chosen as the data points themselves and thus the dictionary is corrupted with noise. This problem is solved in the low rank subspace clustering model which decomposes the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and gross errors. Also, the clustering results of the low rank representation model can be enh"},"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":"1610.07488","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-10-24T16:51:05Z","cross_cats_sorted":[],"title_canon_sha256":"7d748b8f36efa96fdaf27c7eb8ab383c52fee9afa8e8a3eb7959f37fe6388889","abstract_canon_sha256":"dd87f2b65b9fd8f3b8a59b8cdd5ad4cf135c70070857db2807967537c72ec88b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:00:59.606790Z","signature_b64":"3e8xDgvNs3uzl2hDx1zrb/PgnonhuvxNrXtx/kaUxlBzE5O0iichy6NodN0RX1MTAkFjOUWntSOd/4BvX1NOCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"07d9c0d3caa95fd5f9d1828ccff04e737b3d106d24aca1b790575f0ccfeef5b9","last_reissued_at":"2026-05-18T01:00:59.606216Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:00:59.606216Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Laplacian regularized low rank subspace clustering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Yiquan Wu, Yu Song","submitted_at":"2016-10-24T16:51:05Z","abstract_excerpt":"The problem of fitting a union of subspaces to a collection of data points drawn from multiple subspaces is considered in this paper. In the traditional low rank representation model, the dictionary used to represent the data points is chosen as the data points themselves and thus the dictionary is corrupted with noise. This problem is solved in the low rank subspace clustering model which decomposes the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and gross errors. Also, the clustering results of the low rank representation model can be enh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.07488","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":""},"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":"1610.07488","created_at":"2026-05-18T01:00:59.606328+00:00"},{"alias_kind":"arxiv_version","alias_value":"1610.07488v2","created_at":"2026-05-18T01:00:59.606328+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.07488","created_at":"2026-05-18T01:00:59.606328+00:00"},{"alias_kind":"pith_short_12","alias_value":"A7M4BU6KVFP5","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_16","alias_value":"A7M4BU6KVFP5L6OR","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_8","alias_value":"A7M4BU6K","created_at":"2026-05-18T12:30:04.600751+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/A7M4BU6KVFP5L6ORQKGM74COON","json":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON.json","graph_json":"https://pith.science/api/pith-number/A7M4BU6KVFP5L6ORQKGM74COON/graph.json","events_json":"https://pith.science/api/pith-number/A7M4BU6KVFP5L6ORQKGM74COON/events.json","paper":"https://pith.science/paper/A7M4BU6K"},"agent_actions":{"view_html":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON","download_json":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON.json","view_paper":"https://pith.science/paper/A7M4BU6K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1610.07488&json=true","fetch_graph":"https://pith.science/api/pith-number/A7M4BU6KVFP5L6ORQKGM74COON/graph.json","fetch_events":"https://pith.science/api/pith-number/A7M4BU6KVFP5L6ORQKGM74COON/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON/action/storage_attestation","attest_author":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON/action/author_attestation","sign_citation":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON/action/citation_signature","submit_replication":"https://pith.science/pith/A7M4BU6KVFP5L6ORQKGM74COON/action/replication_record"}},"created_at":"2026-05-18T01:00:59.606328+00:00","updated_at":"2026-05-18T01:00:59.606328+00:00"}