{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:HHO4TFRDWTBKFNBD4KQCXJESV4","short_pith_number":"pith:HHO4TFRD","canonical_record":{"source":{"id":"2009.11713","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-09-24T14:16:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"17f462fae2112751bff73eae08d3d55c4cdbc3c8f377308afe42fed8aaff3988","abstract_canon_sha256":"0583cd8c5c89fe36f9ebcdf1bf645d18a82fb2a82880721d52b9ec8d51a57cc7"},"schema_version":"1.0"},"canonical_sha256":"39ddc99623b4c2a2b423e2a02ba492af0b75bf81f6723a427903735b76182f0e","source":{"kind":"arxiv","id":"2009.11713","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.11713","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"arxiv_version","alias_value":"2009.11713v3","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.11713","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"pith_short_12","alias_value":"HHO4TFRDWTBK","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"pith_short_16","alias_value":"HHO4TFRDWTBKFNBD","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"pith_short_8","alias_value":"HHO4TFRD","created_at":"2026-07-05T04:13:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:HHO4TFRDWTBKFNBD4KQCXJESV4","target":"record","payload":{"canonical_record":{"source":{"id":"2009.11713","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-09-24T14:16:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"17f462fae2112751bff73eae08d3d55c4cdbc3c8f377308afe42fed8aaff3988","abstract_canon_sha256":"0583cd8c5c89fe36f9ebcdf1bf645d18a82fb2a82880721d52b9ec8d51a57cc7"},"schema_version":"1.0"},"canonical_sha256":"39ddc99623b4c2a2b423e2a02ba492af0b75bf81f6723a427903735b76182f0e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:13:21.126257Z","signature_b64":"XUWlECHyyrm3mAgxz/m5epbmyxAIJWo3jrV4yHDiN3ynRPgaCr2ei6qV329ZquXjag2u74uk4Aq8cSVlVyXMCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"39ddc99623b4c2a2b423e2a02ba492af0b75bf81f6723a427903735b76182f0e","last_reissued_at":"2026-07-05T04:13:21.125867Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:13:21.125867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2009.11713","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:13:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RMTczgHbmBt4w+q8KZQH4fJ2pNulal5KLkXdHbWqna+ydGtAdFTPcm6I4p7S8U85oVueG63Uiuty+av2Gh5+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T02:46:14.083133Z"},"content_sha256":"4b28da5f8f0ec35a9cdb1783a243f795d08407af6467112621b53d4838233090","schema_version":"1.0","event_id":"sha256:4b28da5f8f0ec35a9cdb1783a243f795d08407af6467112621b53d4838233090"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:HHO4TFRDWTBKFNBD4KQCXJESV4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Jianguo Wu, Ruiyu Xu, Xiaowei Yue, Yongxiang Li","submitted_at":"2020-09-24T14:16:18Z","abstract_excerpt":"High-dimensional streaming data are becoming increasingly ubiquitous in many fields. They often lie in multiple low-dimensional subspaces, and the manifold structures may change abruptly on the time scale due to pattern shift or occurrence of anomalies. However, the problem of detecting the structural changes in a real-time manner has not been well studied. To fill this gap, we propose a dynamic sparse subspace learning approach for online structural change-point detection of high-dimensional streaming data. A novel multiple structural change-point model is proposed and the asymptotic properti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.11713","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2009.11713/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T04:13:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z6Jp3W2Gn9XCNLwwqSMQ2XMHPDIxQo6VzAYFUJWr7GSvEhHOR/marfVt56pRVELjlUm7uVlX6i1zBXGvLtHnAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T02:46:14.083660Z"},"content_sha256":"098a77bead4cd4307bfaca4f92e33ddc3e72822933556b46a80d7225099ba0e6","schema_version":"1.0","event_id":"sha256:098a77bead4cd4307bfaca4f92e33ddc3e72822933556b46a80d7225099ba0e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HHO4TFRDWTBKFNBD4KQCXJESV4/bundle.json","state_url":"https://pith.science/pith/HHO4TFRDWTBKFNBD4KQCXJESV4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HHO4TFRDWTBKFNBD4KQCXJESV4/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":"2026-08-14T02:46:14Z","links":{"resolver":"https://pith.science/pith/HHO4TFRDWTBKFNBD4KQCXJESV4","bundle":"https://pith.science/pith/HHO4TFRDWTBKFNBD4KQCXJESV4/bundle.json","state":"https://pith.science/pith/HHO4TFRDWTBKFNBD4KQCXJESV4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HHO4TFRDWTBKFNBD4KQCXJESV4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:HHO4TFRDWTBKFNBD4KQCXJESV4","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":"0583cd8c5c89fe36f9ebcdf1bf645d18a82fb2a82880721d52b9ec8d51a57cc7","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-09-24T14:16:18Z","title_canon_sha256":"17f462fae2112751bff73eae08d3d55c4cdbc3c8f377308afe42fed8aaff3988"},"schema_version":"1.0","source":{"id":"2009.11713","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.11713","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"arxiv_version","alias_value":"2009.11713v3","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.11713","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"pith_short_12","alias_value":"HHO4TFRDWTBK","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"pith_short_16","alias_value":"HHO4TFRDWTBKFNBD","created_at":"2026-07-05T04:13:21Z"},{"alias_kind":"pith_short_8","alias_value":"HHO4TFRD","created_at":"2026-07-05T04:13:21Z"}],"graph_snapshots":[{"event_id":"sha256:098a77bead4cd4307bfaca4f92e33ddc3e72822933556b46a80d7225099ba0e6","target":"graph","created_at":"2026-07-05T04:13:21Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2009.11713/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"High-dimensional streaming data are becoming increasingly ubiquitous in many fields. They often lie in multiple low-dimensional subspaces, and the manifold structures may change abruptly on the time scale due to pattern shift or occurrence of anomalies. However, the problem of detecting the structural changes in a real-time manner has not been well studied. To fill this gap, we propose a dynamic sparse subspace learning approach for online structural change-point detection of high-dimensional streaming data. A novel multiple structural change-point model is proposed and the asymptotic properti","authors_text":"Jianguo Wu, Ruiyu Xu, Xiaowei Yue, Yongxiang Li","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-09-24T14:16:18Z","title":"Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.11713","kind":"arxiv","version":3},"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":"sha256:4b28da5f8f0ec35a9cdb1783a243f795d08407af6467112621b53d4838233090","target":"record","created_at":"2026-07-05T04:13:21Z","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":"0583cd8c5c89fe36f9ebcdf1bf645d18a82fb2a82880721d52b9ec8d51a57cc7","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-09-24T14:16:18Z","title_canon_sha256":"17f462fae2112751bff73eae08d3d55c4cdbc3c8f377308afe42fed8aaff3988"},"schema_version":"1.0","source":{"id":"2009.11713","kind":"arxiv","version":3}},"canonical_sha256":"39ddc99623b4c2a2b423e2a02ba492af0b75bf81f6723a427903735b76182f0e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"39ddc99623b4c2a2b423e2a02ba492af0b75bf81f6723a427903735b76182f0e","first_computed_at":"2026-07-05T04:13:21.125867Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:13:21.125867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XUWlECHyyrm3mAgxz/m5epbmyxAIJWo3jrV4yHDiN3ynRPgaCr2ei6qV329ZquXjag2u74uk4Aq8cSVlVyXMCw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:13:21.126257Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.11713","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4b28da5f8f0ec35a9cdb1783a243f795d08407af6467112621b53d4838233090","sha256:098a77bead4cd4307bfaca4f92e33ddc3e72822933556b46a80d7225099ba0e6"],"state_sha256":"6e349316b422b675053e8411b799adf314a2afb54c3a954974d6361a1b5d3803"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fLoyJQHf7S+AhujGk1gI/9L3BnG6KY/G+1Zpy4atoVJbxez2icWdioCcFHpVrb8Jp/2I2Uv+72kL/vBSTRbFAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T02:46:14.088902Z","bundle_sha256":"dc605bae5c27305f41e343a33287bb98375d800e7744d0e284d09ecd48703a1b"}}