{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:ONS4YLGZGTSTAUM4V5FWV7GNFO","short_pith_number":"pith:ONS4YLGZ","schema_version":"1.0","canonical_sha256":"7365cc2cd934e530519caf4b6afccd2bb4934aab3a5bbe8a0f54f90713d5308c","source":{"kind":"arxiv","id":"1801.10264","version":2},"attestation_state":"computed","paper":{"title":"Compressed Anomaly Detection with Multiple Mixed Observations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS","eess.SP","math.IT","math.NA","math.OC"],"primary_cat":"cs.IT","authors_text":"Anna Ma, Chenxi Huang, Deanna Needell, Jing Qin, Natalie Durgin, Rachel Grotheer, Shuang Li","submitted_at":"2018-01-31T01:18:33Z","abstract_excerpt":"We consider a collection of independent random variables that are identically distributed, except for a small subset which follows a different, anomalous distribution. We study the problem of detecting which random variables in the collection are governed by the anomalous distribution. Recent work proposes to solve this problem by conducting hypothesis tests based on mixed observations (e.g. linear combinations) of the random variables. Recognizing the connection between taking mixed observations and compressed sensing, we view the problem as recovering the \"support\" (index set) of the anomalo"},"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":"1801.10264","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2018-01-31T01:18:33Z","cross_cats_sorted":["cs.DS","eess.SP","math.IT","math.NA","math.OC"],"title_canon_sha256":"db8db4e5ec4bbbfc28fb640b946f7f816295e337794e67c2624d0f8283f35d10","abstract_canon_sha256":"fc56c86b9a1c63b5eb53641343a93b5847461637b7a5ec6c35ff1d2283c3bf8e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:12:48.401029Z","signature_b64":"EBFuYolgkJZQcqfsTSxId4yBCwVSQY6piJftgLP+ykBfe1/m8OlCplMK2zo9vlOaPmKSxAYfbpQEaXHbu+VOBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7365cc2cd934e530519caf4b6afccd2bb4934aab3a5bbe8a0f54f90713d5308c","last_reissued_at":"2026-05-18T00:12:48.400527Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:12:48.400527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Compressed Anomaly Detection with Multiple Mixed Observations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS","eess.SP","math.IT","math.NA","math.OC"],"primary_cat":"cs.IT","authors_text":"Anna Ma, Chenxi Huang, Deanna Needell, Jing Qin, Natalie Durgin, Rachel Grotheer, Shuang Li","submitted_at":"2018-01-31T01:18:33Z","abstract_excerpt":"We consider a collection of independent random variables that are identically distributed, except for a small subset which follows a different, anomalous distribution. We study the problem of detecting which random variables in the collection are governed by the anomalous distribution. Recent work proposes to solve this problem by conducting hypothesis tests based on mixed observations (e.g. linear combinations) of the random variables. Recognizing the connection between taking mixed observations and compressed sensing, we view the problem as recovering the \"support\" (index set) of the anomalo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.10264","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1801.10264","created_at":"2026-05-18T00:12:48.400592+00:00"},{"alias_kind":"arxiv_version","alias_value":"1801.10264v2","created_at":"2026-05-18T00:12:48.400592+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.10264","created_at":"2026-05-18T00:12:48.400592+00:00"},{"alias_kind":"pith_short_12","alias_value":"ONS4YLGZGTST","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_16","alias_value":"ONS4YLGZGTSTAUM4","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_8","alias_value":"ONS4YLGZ","created_at":"2026-05-18T12:32:43.782077+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/ONS4YLGZGTSTAUM4V5FWV7GNFO","json":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO.json","graph_json":"https://pith.science/api/pith-number/ONS4YLGZGTSTAUM4V5FWV7GNFO/graph.json","events_json":"https://pith.science/api/pith-number/ONS4YLGZGTSTAUM4V5FWV7GNFO/events.json","paper":"https://pith.science/paper/ONS4YLGZ"},"agent_actions":{"view_html":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO","download_json":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO.json","view_paper":"https://pith.science/paper/ONS4YLGZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1801.10264&json=true","fetch_graph":"https://pith.science/api/pith-number/ONS4YLGZGTSTAUM4V5FWV7GNFO/graph.json","fetch_events":"https://pith.science/api/pith-number/ONS4YLGZGTSTAUM4V5FWV7GNFO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO/action/storage_attestation","attest_author":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO/action/author_attestation","sign_citation":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO/action/citation_signature","submit_replication":"https://pith.science/pith/ONS4YLGZGTSTAUM4V5FWV7GNFO/action/replication_record"}},"created_at":"2026-05-18T00:12:48.400592+00:00","updated_at":"2026-05-18T00:12:48.400592+00:00"}