{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:HJ2362MEUUT5T6D4YFEKYLGFZF","short_pith_number":"pith:HJ2362ME","schema_version":"1.0","canonical_sha256":"3a75bf6984a527d9f87cc148ac2cc5c942c7fafb68b6fcce53f894f28b1cb4f8","source":{"kind":"arxiv","id":"1711.11220","version":1},"attestation_state":"computed","paper":{"title":"RANSAC Algorithms for Subspace Recovery and Subspace Clustering","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.CO","stat.TH"],"primary_cat":"math.ST","authors_text":"Ery Arias-Castro, Jue Wang","submitted_at":"2017-11-30T04:29:46Z","abstract_excerpt":"We consider the RANSAC algorithm in the context of subspace recovery and subspace clustering. We derive some theory and perform some numerical experiments. We also draw some correspondences with the methods of Hardt and Moitra (2013) and Chen and Lerman (2009b)."},"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":"1711.11220","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2017-11-30T04:29:46Z","cross_cats_sorted":["stat.CO","stat.TH"],"title_canon_sha256":"3b437f8ca6d41be93e6c0b1ded51e49c2c99645f7eacae89ffebeaef7da5aed9","abstract_canon_sha256":"d40ab029ee7929dfbec57ff7176c111d43286faa8ae6bc319e187b9a4766f7f2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:12.178363Z","signature_b64":"nTFhCbDKUpvRV6Jo9S3s83CQBwLfdbDd3pXy3oKe9PJJIftfQ9PTPidRVKkIxredJWUxHSQ707SNLCn27osHDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a75bf6984a527d9f87cc148ac2cc5c942c7fafb68b6fcce53f894f28b1cb4f8","last_reissued_at":"2026-05-18T00:29:12.177729Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:12.177729Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RANSAC Algorithms for Subspace Recovery and Subspace Clustering","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.CO","stat.TH"],"primary_cat":"math.ST","authors_text":"Ery Arias-Castro, Jue Wang","submitted_at":"2017-11-30T04:29:46Z","abstract_excerpt":"We consider the RANSAC algorithm in the context of subspace recovery and subspace clustering. We derive some theory and perform some numerical experiments. We also draw some correspondences with the methods of Hardt and Moitra (2013) and Chen and Lerman (2009b)."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.11220","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":""},"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":"1711.11220","created_at":"2026-05-18T00:29:12.177816+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.11220v1","created_at":"2026-05-18T00:29:12.177816+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.11220","created_at":"2026-05-18T00:29:12.177816+00:00"},{"alias_kind":"pith_short_12","alias_value":"HJ2362MEUUT5","created_at":"2026-05-18T12:31:18.294218+00:00"},{"alias_kind":"pith_short_16","alias_value":"HJ2362MEUUT5T6D4","created_at":"2026-05-18T12:31:18.294218+00:00"},{"alias_kind":"pith_short_8","alias_value":"HJ2362ME","created_at":"2026-05-18T12:31:18.294218+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/HJ2362MEUUT5T6D4YFEKYLGFZF","json":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF.json","graph_json":"https://pith.science/api/pith-number/HJ2362MEUUT5T6D4YFEKYLGFZF/graph.json","events_json":"https://pith.science/api/pith-number/HJ2362MEUUT5T6D4YFEKYLGFZF/events.json","paper":"https://pith.science/paper/HJ2362ME"},"agent_actions":{"view_html":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF","download_json":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF.json","view_paper":"https://pith.science/paper/HJ2362ME","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.11220&json=true","fetch_graph":"https://pith.science/api/pith-number/HJ2362MEUUT5T6D4YFEKYLGFZF/graph.json","fetch_events":"https://pith.science/api/pith-number/HJ2362MEUUT5T6D4YFEKYLGFZF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF/action/storage_attestation","attest_author":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF/action/author_attestation","sign_citation":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF/action/citation_signature","submit_replication":"https://pith.science/pith/HJ2362MEUUT5T6D4YFEKYLGFZF/action/replication_record"}},"created_at":"2026-05-18T00:29:12.177816+00:00","updated_at":"2026-05-18T00:29:12.177816+00:00"}