{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2010:RYSEBH5GJMGW4GUXZVPU2T6FXA","short_pith_number":"pith:RYSEBH5G","canonical_record":{"source":{"id":"1012.0365","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2010-12-02T01:59:21Z","cross_cats_sorted":["cs.AI","math.OC"],"title_canon_sha256":"532245f3e22d8652c2f547cc96dbec8695e1170f197fd2e27f648945978f3c1e","abstract_canon_sha256":"67c1f543bc7748b0418f350f8a74df25d74f0157cd615869d575a18250a9d7e2"},"schema_version":"1.0"},"canonical_sha256":"8e24409fa64b0d6e1a97cd5f4d4fc5b8055903f2fdea1c352067a74a31c5617b","source":{"kind":"arxiv","id":"1012.0365","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1012.0365","created_at":"2026-05-18T04:32:33Z"},{"alias_kind":"arxiv_version","alias_value":"1012.0365v2","created_at":"2026-05-18T04:32:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1012.0365","created_at":"2026-05-18T04:32:33Z"},{"alias_kind":"pith_short_12","alias_value":"RYSEBH5GJMGW","created_at":"2026-05-18T12:26:13Z"},{"alias_kind":"pith_short_16","alias_value":"RYSEBH5GJMGW4GUX","created_at":"2026-05-18T12:26:13Z"},{"alias_kind":"pith_short_8","alias_value":"RYSEBH5G","created_at":"2026-05-18T12:26:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2010:RYSEBH5GJMGW4GUXZVPU2T6FXA","target":"record","payload":{"canonical_record":{"source":{"id":"1012.0365","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2010-12-02T01:59:21Z","cross_cats_sorted":["cs.AI","math.OC"],"title_canon_sha256":"532245f3e22d8652c2f547cc96dbec8695e1170f197fd2e27f648945978f3c1e","abstract_canon_sha256":"67c1f543bc7748b0418f350f8a74df25d74f0157cd615869d575a18250a9d7e2"},"schema_version":"1.0"},"canonical_sha256":"8e24409fa64b0d6e1a97cd5f4d4fc5b8055903f2fdea1c352067a74a31c5617b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:32:33.705167Z","signature_b64":"ELvUswjcoNeItFH06tD5J21k9PyIGLrJ03AUJPcKe5ksrujkwj2laSbgb5kcb6q6CfnbaoANqo+sMltM1BwQAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e24409fa64b0d6e1a97cd5f4d4fc5b8055903f2fdea1c352067a74a31c5617b","last_reissued_at":"2026-05-18T04:32:33.704532Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:32:33.704532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1012.0365","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":"2026-05-18T04:32:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qrODUXtBAuFj8pxGEsZJRXYkVVCVoJpbz2EASAln/7XOzmrZUTVcH2n5m37Ua2M/kubOp9XzO08y9epocEsMBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T16:57:37.029954Z"},"content_sha256":"95474eba6c1a6bcc332a40c2ec66df5e1bdf05378848dd6edaa672e006ecf105","schema_version":"1.0","event_id":"sha256:95474eba6c1a6bcc332a40c2ec66df5e1bdf05378848dd6edaa672e006ecf105"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2010:RYSEBH5GJMGW4GUXZVPU2T6FXA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Block Lanczos with Warm Start Technique for Accelerating Nuclear Norm Minimization Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","math.OC"],"primary_cat":"cs.NA","authors_text":"Siming Wei, Zhouchen Lin","submitted_at":"2010-12-02T01:59:21Z","abstract_excerpt":"Recent years have witnessed the popularity of using rank minimization as a regularizer for various signal processing and machine learning problems. As rank minimization problems are often converted to nuclear norm minimization (NNM) problems, they have to be solved iteratively and each iteration requires computing a singular value decomposition (SVD). Therefore, their solution suffers from the high computation cost of multiple SVDs. To relieve this issue, we propose using the block Lanczos method to compute the partial SVDs, where the principal singular subspaces obtained in the previous itera"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1012.0365","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:32:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+tkdI0ux/F/NgfwWEf54eXSlWe53QfjqsinfnSD/udXYmIPGf2zRWSKaLAKPn8ddZsfjHUoefleASwf7TOPZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T16:57:37.030641Z"},"content_sha256":"edf1bc0dcc93cb3016e995ddeb3dafd27f1061c998106f7bff4a0d0afef8f4c1","schema_version":"1.0","event_id":"sha256:edf1bc0dcc93cb3016e995ddeb3dafd27f1061c998106f7bff4a0d0afef8f4c1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RYSEBH5GJMGW4GUXZVPU2T6FXA/bundle.json","state_url":"https://pith.science/pith/RYSEBH5GJMGW4GUXZVPU2T6FXA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RYSEBH5GJMGW4GUXZVPU2T6FXA/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":"2026-05-26T16:57:37Z","links":{"resolver":"https://pith.science/pith/RYSEBH5GJMGW4GUXZVPU2T6FXA","bundle":"https://pith.science/pith/RYSEBH5GJMGW4GUXZVPU2T6FXA/bundle.json","state":"https://pith.science/pith/RYSEBH5GJMGW4GUXZVPU2T6FXA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RYSEBH5GJMGW4GUXZVPU2T6FXA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2010:RYSEBH5GJMGW4GUXZVPU2T6FXA","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":"67c1f543bc7748b0418f350f8a74df25d74f0157cd615869d575a18250a9d7e2","cross_cats_sorted":["cs.AI","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2010-12-02T01:59:21Z","title_canon_sha256":"532245f3e22d8652c2f547cc96dbec8695e1170f197fd2e27f648945978f3c1e"},"schema_version":"1.0","source":{"id":"1012.0365","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1012.0365","created_at":"2026-05-18T04:32:33Z"},{"alias_kind":"arxiv_version","alias_value":"1012.0365v2","created_at":"2026-05-18T04:32:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1012.0365","created_at":"2026-05-18T04:32:33Z"},{"alias_kind":"pith_short_12","alias_value":"RYSEBH5GJMGW","created_at":"2026-05-18T12:26:13Z"},{"alias_kind":"pith_short_16","alias_value":"RYSEBH5GJMGW4GUX","created_at":"2026-05-18T12:26:13Z"},{"alias_kind":"pith_short_8","alias_value":"RYSEBH5G","created_at":"2026-05-18T12:26:13Z"}],"graph_snapshots":[{"event_id":"sha256:edf1bc0dcc93cb3016e995ddeb3dafd27f1061c998106f7bff4a0d0afef8f4c1","target":"graph","created_at":"2026-05-18T04:32:33Z","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":"Recent years have witnessed the popularity of using rank minimization as a regularizer for various signal processing and machine learning problems. As rank minimization problems are often converted to nuclear norm minimization (NNM) problems, they have to be solved iteratively and each iteration requires computing a singular value decomposition (SVD). Therefore, their solution suffers from the high computation cost of multiple SVDs. To relieve this issue, we propose using the block Lanczos method to compute the partial SVDs, where the principal singular subspaces obtained in the previous itera","authors_text":"Siming Wei, Zhouchen Lin","cross_cats":["cs.AI","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2010-12-02T01:59:21Z","title":"A Block Lanczos with Warm Start Technique for Accelerating Nuclear Norm Minimization Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1012.0365","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":"sha256:95474eba6c1a6bcc332a40c2ec66df5e1bdf05378848dd6edaa672e006ecf105","target":"record","created_at":"2026-05-18T04:32:33Z","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":"67c1f543bc7748b0418f350f8a74df25d74f0157cd615869d575a18250a9d7e2","cross_cats_sorted":["cs.AI","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2010-12-02T01:59:21Z","title_canon_sha256":"532245f3e22d8652c2f547cc96dbec8695e1170f197fd2e27f648945978f3c1e"},"schema_version":"1.0","source":{"id":"1012.0365","kind":"arxiv","version":2}},"canonical_sha256":"8e24409fa64b0d6e1a97cd5f4d4fc5b8055903f2fdea1c352067a74a31c5617b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e24409fa64b0d6e1a97cd5f4d4fc5b8055903f2fdea1c352067a74a31c5617b","first_computed_at":"2026-05-18T04:32:33.704532Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:32:33.704532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ELvUswjcoNeItFH06tD5J21k9PyIGLrJ03AUJPcKe5ksrujkwj2laSbgb5kcb6q6CfnbaoANqo+sMltM1BwQAA==","signature_status":"signed_v1","signed_at":"2026-05-18T04:32:33.705167Z","signed_message":"canonical_sha256_bytes"},"source_id":"1012.0365","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:95474eba6c1a6bcc332a40c2ec66df5e1bdf05378848dd6edaa672e006ecf105","sha256:edf1bc0dcc93cb3016e995ddeb3dafd27f1061c998106f7bff4a0d0afef8f4c1"],"state_sha256":"9220e271c9d99f528ba89d34a9f56c267e8eb4b8972ea1d7f5084dae531674de"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ofaHLwJGnZJwe8/vaSlM5qyp0Na95kK/dIrzaQ+V3dslgr4pcykwKu0c6TcPqu9Mim0zZoZKHv7TKOGEvYbDBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T16:57:37.034493Z","bundle_sha256":"fc0e20b0727e21ac91a931a557d4d49d671a54b9903743e6b13af8ea0f5a0bab"}}