{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:K4ETU545SQOKMCACR36QMXW7N3","short_pith_number":"pith:K4ETU545","schema_version":"1.0","canonical_sha256":"57093a779d941ca608028efd065edf6ec951879a42346ec3942c9dd07fcd2612","source":{"kind":"arxiv","id":"1606.02608","version":1},"attestation_state":"computed","paper":{"title":"Fast and Extensible Online Multivariate Kernel Density Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"David Martins de Matos, Jaime Ferreira, Ricardo Ribeiro","submitted_at":"2016-06-08T15:39:17Z","abstract_excerpt":"We present xokde++, a state-of-the-art online kernel density estimation approach that maintains Gaussian mixture models input data streams. The approach follows state-of-the-art work on online density estimation, but was redesigned with computational efficiency, numerical robustness, and extensibility in mind. Our approach produces comparable or better results than the current state-of-the-art, while achieving significant computational performance gains and improved numerical stability. The use of diagonal covariance Gaussian kernels, which further improve performance and stability, at a small"},"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":"1606.02608","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-06-08T15:39:17Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"1dae60c1f48747eced8c0aa811c16c554ed07d6c45c1a289865fcb4bca70d640","abstract_canon_sha256":"69cd2c29cc6df2f0ddad9835a9a7fb1f837d768d02ef300f1fbf25ad8eceba8a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:12:40.990093Z","signature_b64":"0HyWi49qSoVH+JokCOTlZ6klgRY0JkhqP7dK5P391CsNRnbfW3CmCq+bOX6/NqLHzHQNOYoUHAm3kOz5Y5IaDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"57093a779d941ca608028efd065edf6ec951879a42346ec3942c9dd07fcd2612","last_reissued_at":"2026-05-18T01:12:40.989706Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:12:40.989706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast and Extensible Online Multivariate Kernel Density Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"David Martins de Matos, Jaime Ferreira, Ricardo Ribeiro","submitted_at":"2016-06-08T15:39:17Z","abstract_excerpt":"We present xokde++, a state-of-the-art online kernel density estimation approach that maintains Gaussian mixture models input data streams. The approach follows state-of-the-art work on online density estimation, but was redesigned with computational efficiency, numerical robustness, and extensibility in mind. Our approach produces comparable or better results than the current state-of-the-art, while achieving significant computational performance gains and improved numerical stability. The use of diagonal covariance Gaussian kernels, which further improve performance and stability, at a small"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.02608","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1606.02608","created_at":"2026-05-18T01:12:40.989762+00:00"},{"alias_kind":"arxiv_version","alias_value":"1606.02608v1","created_at":"2026-05-18T01:12:40.989762+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.02608","created_at":"2026-05-18T01:12:40.989762+00:00"},{"alias_kind":"pith_short_12","alias_value":"K4ETU545SQOK","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_16","alias_value":"K4ETU545SQOKMCAC","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_8","alias_value":"K4ETU545","created_at":"2026-05-18T12:30:25.849896+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/K4ETU545SQOKMCACR36QMXW7N3","json":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3.json","graph_json":"https://pith.science/api/pith-number/K4ETU545SQOKMCACR36QMXW7N3/graph.json","events_json":"https://pith.science/api/pith-number/K4ETU545SQOKMCACR36QMXW7N3/events.json","paper":"https://pith.science/paper/K4ETU545"},"agent_actions":{"view_html":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3","download_json":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3.json","view_paper":"https://pith.science/paper/K4ETU545","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1606.02608&json=true","fetch_graph":"https://pith.science/api/pith-number/K4ETU545SQOKMCACR36QMXW7N3/graph.json","fetch_events":"https://pith.science/api/pith-number/K4ETU545SQOKMCACR36QMXW7N3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3/action/storage_attestation","attest_author":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3/action/author_attestation","sign_citation":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3/action/citation_signature","submit_replication":"https://pith.science/pith/K4ETU545SQOKMCACR36QMXW7N3/action/replication_record"}},"created_at":"2026-05-18T01:12:40.989762+00:00","updated_at":"2026-05-18T01:12:40.989762+00:00"}