{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:OKPTSP5S3CKCS6PERYVOTY6GA7","short_pith_number":"pith:OKPTSP5S","canonical_record":{"source":{"id":"1108.5359","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2011-08-26T17:40:30Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"b719633bbd8e00ae36584c25b1427145e2255b7d00670e8b99c983c6d5afefe2","abstract_canon_sha256":"767d6a4339e2b13c292d084a52ab33445bf49e213722ad00defa1decd68c6027"},"schema_version":"1.0"},"canonical_sha256":"729f393fb2d8942979e48e2ae9e3c607f2da0661ea0b4cebc79f985866b72d63","source":{"kind":"arxiv","id":"1108.5359","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1108.5359","created_at":"2026-05-18T03:56:22Z"},{"alias_kind":"arxiv_version","alias_value":"1108.5359v4","created_at":"2026-05-18T03:56:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.5359","created_at":"2026-05-18T03:56:22Z"},{"alias_kind":"pith_short_12","alias_value":"OKPTSP5S3CKC","created_at":"2026-05-18T12:26:37Z"},{"alias_kind":"pith_short_16","alias_value":"OKPTSP5S3CKCS6PE","created_at":"2026-05-18T12:26:37Z"},{"alias_kind":"pith_short_8","alias_value":"OKPTSP5S","created_at":"2026-05-18T12:26:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:OKPTSP5S3CKCS6PERYVOTY6GA7","target":"record","payload":{"canonical_record":{"source":{"id":"1108.5359","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2011-08-26T17:40:30Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"b719633bbd8e00ae36584c25b1427145e2255b7d00670e8b99c983c6d5afefe2","abstract_canon_sha256":"767d6a4339e2b13c292d084a52ab33445bf49e213722ad00defa1decd68c6027"},"schema_version":"1.0"},"canonical_sha256":"729f393fb2d8942979e48e2ae9e3c607f2da0661ea0b4cebc79f985866b72d63","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:56:22.545634Z","signature_b64":"FpBKOjEklc/6q/xjnyGLD6z1WxLs91bblfup/nCHLFa1McOPQVwV4YksfSZxzDl0x/06Lg0SFlPYV+RAhoe8Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"729f393fb2d8942979e48e2ae9e3c607f2da0661ea0b4cebc79f985866b72d63","last_reissued_at":"2026-05-18T03:56:22.544973Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:56:22.544973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1108.5359","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:56:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4JteNVnxSz19t+oS2SaWGM2/dpUispK824TeYZ7zibgTeM/+6gO7XPMAhgNtB4oKJ34MF1QxwNNq5M9fHgECDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T03:36:13.620107Z"},"content_sha256":"c045411af045f326f7247301e3908ac497a6c5bc2c4604407abd83ba4428736f","schema_version":"1.0","event_id":"sha256:c045411af045f326f7247301e3908ac497a6c5bc2c4604407abd83ba4428736f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:OKPTSP5S3CKCS6PERYVOTY6GA7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Solving Principal Component Pursuit in Linear Time via $l_1$ Filtering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.NA","authors_text":"Risheng Liu, Siming Wei, Zhixun Su, Zhouchen Lin","submitted_at":"2011-08-26T17:40:30Z","abstract_excerpt":"In the past decades, exactly recovering the intrinsic data structure from corrupted observations, which is known as robust principal component analysis (RPCA), has attracted tremendous interests and found many applications in computer vision. Recently, this problem has been formulated as recovering a low-rank component and a sparse component from the observed data matrix. It is proved that under some suitable conditions, this problem can be exactly solved by principal component pursuit (PCP), i.e., minimizing a combination of nuclear norm and $l_1$ norm. Most of the existing methods for solvin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.5359","kind":"arxiv","version":4},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:56:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oFbDE8F0egzQZFN+fMrqnbFCXbfj7hO0+CFVciLOxg3wkPQtyq95/axvdsYB3yj6KOF5YIZqXpotB8cyA04VAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T03:36:13.620919Z"},"content_sha256":"076756ce10a494184478dffe9d79f6b6bf2411f414098348572a28376bf7872c","schema_version":"1.0","event_id":"sha256:076756ce10a494184478dffe9d79f6b6bf2411f414098348572a28376bf7872c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OKPTSP5S3CKCS6PERYVOTY6GA7/bundle.json","state_url":"https://pith.science/pith/OKPTSP5S3CKCS6PERYVOTY6GA7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OKPTSP5S3CKCS6PERYVOTY6GA7/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":"2026-05-20T03:36:13Z","links":{"resolver":"https://pith.science/pith/OKPTSP5S3CKCS6PERYVOTY6GA7","bundle":"https://pith.science/pith/OKPTSP5S3CKCS6PERYVOTY6GA7/bundle.json","state":"https://pith.science/pith/OKPTSP5S3CKCS6PERYVOTY6GA7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OKPTSP5S3CKCS6PERYVOTY6GA7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:OKPTSP5S3CKCS6PERYVOTY6GA7","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":"767d6a4339e2b13c292d084a52ab33445bf49e213722ad00defa1decd68c6027","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2011-08-26T17:40:30Z","title_canon_sha256":"b719633bbd8e00ae36584c25b1427145e2255b7d00670e8b99c983c6d5afefe2"},"schema_version":"1.0","source":{"id":"1108.5359","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1108.5359","created_at":"2026-05-18T03:56:22Z"},{"alias_kind":"arxiv_version","alias_value":"1108.5359v4","created_at":"2026-05-18T03:56:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.5359","created_at":"2026-05-18T03:56:22Z"},{"alias_kind":"pith_short_12","alias_value":"OKPTSP5S3CKC","created_at":"2026-05-18T12:26:37Z"},{"alias_kind":"pith_short_16","alias_value":"OKPTSP5S3CKCS6PE","created_at":"2026-05-18T12:26:37Z"},{"alias_kind":"pith_short_8","alias_value":"OKPTSP5S","created_at":"2026-05-18T12:26:37Z"}],"graph_snapshots":[{"event_id":"sha256:076756ce10a494184478dffe9d79f6b6bf2411f414098348572a28376bf7872c","target":"graph","created_at":"2026-05-18T03:56:22Z","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"},"paper":{"abstract_excerpt":"In the past decades, exactly recovering the intrinsic data structure from corrupted observations, which is known as robust principal component analysis (RPCA), has attracted tremendous interests and found many applications in computer vision. Recently, this problem has been formulated as recovering a low-rank component and a sparse component from the observed data matrix. It is proved that under some suitable conditions, this problem can be exactly solved by principal component pursuit (PCP), i.e., minimizing a combination of nuclear norm and $l_1$ norm. Most of the existing methods for solvin","authors_text":"Risheng Liu, Siming Wei, Zhixun Su, Zhouchen Lin","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2011-08-26T17:40:30Z","title":"Solving Principal Component Pursuit in Linear Time via $l_1$ Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.5359","kind":"arxiv","version":4},"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:c045411af045f326f7247301e3908ac497a6c5bc2c4604407abd83ba4428736f","target":"record","created_at":"2026-05-18T03:56:22Z","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":"767d6a4339e2b13c292d084a52ab33445bf49e213722ad00defa1decd68c6027","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2011-08-26T17:40:30Z","title_canon_sha256":"b719633bbd8e00ae36584c25b1427145e2255b7d00670e8b99c983c6d5afefe2"},"schema_version":"1.0","source":{"id":"1108.5359","kind":"arxiv","version":4}},"canonical_sha256":"729f393fb2d8942979e48e2ae9e3c607f2da0661ea0b4cebc79f985866b72d63","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"729f393fb2d8942979e48e2ae9e3c607f2da0661ea0b4cebc79f985866b72d63","first_computed_at":"2026-05-18T03:56:22.544973Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:56:22.544973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FpBKOjEklc/6q/xjnyGLD6z1WxLs91bblfup/nCHLFa1McOPQVwV4YksfSZxzDl0x/06Lg0SFlPYV+RAhoe8Cw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:56:22.545634Z","signed_message":"canonical_sha256_bytes"},"source_id":"1108.5359","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c045411af045f326f7247301e3908ac497a6c5bc2c4604407abd83ba4428736f","sha256:076756ce10a494184478dffe9d79f6b6bf2411f414098348572a28376bf7872c"],"state_sha256":"571ffacbbc3585c4e9af16a97bec6d6fe5ce10c402f47b8ff5d56ddf0ce1c0c6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1OQiQ7dtrFM/kvFtr/IpbyMP57BLpsX1MufhExle8RpWu8QQnyWIAOjoZFlOjrpIRl327fM+VRurU04LyRE3Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T03:36:13.625978Z","bundle_sha256":"d9ce81d586bed4c7ca46c7326ca5a0c43871bfc6f125bd9bb03f6c7a94517e1f"}}