{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:G26RQCNWTMQWG3GEZZRZUDMGZ6","short_pith_number":"pith:G26RQCNW","canonical_record":{"source":{"id":"1709.04836","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-14T15:06:21Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"7314f52b9749fb1d597272b4806499d2966198bbf0e711685bb4574b8631a44b","abstract_canon_sha256":"9e8c72f685ebfdf4ef28b583133146e89a89d14a4094cfa6a67c56e350bc535b"},"schema_version":"1.0"},"canonical_sha256":"36bd1809b69b21636cc4ce639a0d86cf9a87a699d732288aff1f8be53fc44824","source":{"kind":"arxiv","id":"1709.04836","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.04836","created_at":"2026-05-18T00:35:09Z"},{"alias_kind":"arxiv_version","alias_value":"1709.04836v1","created_at":"2026-05-18T00:35:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.04836","created_at":"2026-05-18T00:35:09Z"},{"alias_kind":"pith_short_12","alias_value":"G26RQCNWTMQW","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"G26RQCNWTMQWG3GE","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"G26RQCNW","created_at":"2026-05-18T12:31:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:G26RQCNWTMQWG3GEZZRZUDMGZ6","target":"record","payload":{"canonical_record":{"source":{"id":"1709.04836","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-14T15:06:21Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"7314f52b9749fb1d597272b4806499d2966198bbf0e711685bb4574b8631a44b","abstract_canon_sha256":"9e8c72f685ebfdf4ef28b583133146e89a89d14a4094cfa6a67c56e350bc535b"},"schema_version":"1.0"},"canonical_sha256":"36bd1809b69b21636cc4ce639a0d86cf9a87a699d732288aff1f8be53fc44824","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:09.871430Z","signature_b64":"nZjXY2NhrJmFdnkgIB8Jvu1dA3fomlmHw1ah+G63Xm/7CpHk37nSPCHxsVNcyn7lbNGJx64O23rK5MgsJvO8CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36bd1809b69b21636cc4ce639a0d86cf9a87a699d732288aff1f8be53fc44824","last_reissued_at":"2026-05-18T00:35:09.871015Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:09.871015Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.04836","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":"2026-05-18T00:35:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Bi8ZF9IVSY8WSFyDHgEAMyG1kB88HOG0O7zlXF0TFxafT+KjnY4XEkhys+hPjYBwnTMbA9gMG4UkL56kUr32Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:44:48.051191Z"},"content_sha256":"45b223cd41621c50307f8168042b8be053518a6644342848a59b8603c8f91744","schema_version":"1.0","event_id":"sha256:45b223cd41621c50307f8168042b8be053518a6644342848a59b8603c8f91744"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:G26RQCNWTMQWG3GEZZRZUDMGZ6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Informed Non-convex Robust Principal Component Analysis with Features","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"stat.ML","authors_text":"Jiankang Deng, Niannan Xue, Stefanos Zafeiriou, Yannis Panagakis","submitted_at":"2017-09-14T15:06:21Z","abstract_excerpt":"We revisit the problem of robust principal component analysis with features acting as prior side information. To this aim, a novel, elegant, non-convex optimization approach is proposed to decompose a given observation matrix into a low-rank core and the corresponding sparse residual. Rigorous theoretical analysis of the proposed algorithm results in exact recovery guarantees with low computational complexity. Aptly designed synthetic experiments demonstrate that our method is the first to wholly harness the power of non-convexity over convexity in terms of both recoverability and speed. That "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.04836","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:35:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E+OIovtEFrs8OTIv37LNHh0mYzlt0QWJVjzEEkktNE0J8zA60PIVVSUz/UCeEgnINfgwd8PcmMsY7V5FP1kYBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:44:48.051880Z"},"content_sha256":"09c86baefcf2294c57ba7cb12666d26fb7b815ef1ff7eedf971740d7b23c7581","schema_version":"1.0","event_id":"sha256:09c86baefcf2294c57ba7cb12666d26fb7b815ef1ff7eedf971740d7b23c7581"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G26RQCNWTMQWG3GEZZRZUDMGZ6/bundle.json","state_url":"https://pith.science/pith/G26RQCNWTMQWG3GEZZRZUDMGZ6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G26RQCNWTMQWG3GEZZRZUDMGZ6/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":"2026-05-29T15:44:48Z","links":{"resolver":"https://pith.science/pith/G26RQCNWTMQWG3GEZZRZUDMGZ6","bundle":"https://pith.science/pith/G26RQCNWTMQWG3GEZZRZUDMGZ6/bundle.json","state":"https://pith.science/pith/G26RQCNWTMQWG3GEZZRZUDMGZ6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G26RQCNWTMQWG3GEZZRZUDMGZ6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:G26RQCNWTMQWG3GEZZRZUDMGZ6","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":"9e8c72f685ebfdf4ef28b583133146e89a89d14a4094cfa6a67c56e350bc535b","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-14T15:06:21Z","title_canon_sha256":"7314f52b9749fb1d597272b4806499d2966198bbf0e711685bb4574b8631a44b"},"schema_version":"1.0","source":{"id":"1709.04836","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.04836","created_at":"2026-05-18T00:35:09Z"},{"alias_kind":"arxiv_version","alias_value":"1709.04836v1","created_at":"2026-05-18T00:35:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.04836","created_at":"2026-05-18T00:35:09Z"},{"alias_kind":"pith_short_12","alias_value":"G26RQCNWTMQW","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"G26RQCNWTMQWG3GE","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"G26RQCNW","created_at":"2026-05-18T12:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:09c86baefcf2294c57ba7cb12666d26fb7b815ef1ff7eedf971740d7b23c7581","target":"graph","created_at":"2026-05-18T00:35:09Z","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":"We revisit the problem of robust principal component analysis with features acting as prior side information. To this aim, a novel, elegant, non-convex optimization approach is proposed to decompose a given observation matrix into a low-rank core and the corresponding sparse residual. Rigorous theoretical analysis of the proposed algorithm results in exact recovery guarantees with low computational complexity. Aptly designed synthetic experiments demonstrate that our method is the first to wholly harness the power of non-convexity over convexity in terms of both recoverability and speed. That ","authors_text":"Jiankang Deng, Niannan Xue, Stefanos Zafeiriou, Yannis Panagakis","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-14T15:06:21Z","title":"Informed Non-convex Robust Principal Component Analysis with Features"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.04836","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":"sha256:45b223cd41621c50307f8168042b8be053518a6644342848a59b8603c8f91744","target":"record","created_at":"2026-05-18T00:35:09Z","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":"9e8c72f685ebfdf4ef28b583133146e89a89d14a4094cfa6a67c56e350bc535b","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-14T15:06:21Z","title_canon_sha256":"7314f52b9749fb1d597272b4806499d2966198bbf0e711685bb4574b8631a44b"},"schema_version":"1.0","source":{"id":"1709.04836","kind":"arxiv","version":1}},"canonical_sha256":"36bd1809b69b21636cc4ce639a0d86cf9a87a699d732288aff1f8be53fc44824","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36bd1809b69b21636cc4ce639a0d86cf9a87a699d732288aff1f8be53fc44824","first_computed_at":"2026-05-18T00:35:09.871015Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:35:09.871015Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nZjXY2NhrJmFdnkgIB8Jvu1dA3fomlmHw1ah+G63Xm/7CpHk37nSPCHxsVNcyn7lbNGJx64O23rK5MgsJvO8CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:35:09.871430Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.04836","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:45b223cd41621c50307f8168042b8be053518a6644342848a59b8603c8f91744","sha256:09c86baefcf2294c57ba7cb12666d26fb7b815ef1ff7eedf971740d7b23c7581"],"state_sha256":"92a50641814324845f19757c1a74a866d695a91ead720acaf2f2cb5fff4394df"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YrlkAp0w5fgJywFIN6DXKuioLfIa7ZTmLFoVXqWBKAsAXrkUAPip1+ODi+JXjjPX47Acvq5fB2fq6GtcbNQUDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T15:44:48.055614Z","bundle_sha256":"847558b5ebfe36e9eefb6c9c10b753af2c805044b9bd49971c329cb5273d4038"}}