{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:63QFHPGK5C4AJU25NNYFAAW67Q","short_pith_number":"pith:63QFHPGK","schema_version":"1.0","canonical_sha256":"f6e053bccae8b804d35d6b705002defc08f361240af1a29a4cb042cb5cc8e904","source":{"kind":"arxiv","id":"1612.04740","version":3},"attestation_state":"computed","paper":{"title":"Consistent change-point detection with kernels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Damien Garreau, Sylvain Arlot","submitted_at":"2016-12-14T17:28:17Z","abstract_excerpt":"In this paper we study the kernel change-point algorithm (KCP) proposed by Arlot, Celisse and Harchaoui (2012), which aims at locating an unknown number of change-points in the distribution of a sequence of independent data taking values in an arbitrary set. The change-points are selected by model selection with a penalized kernel empirical criterion. We provide a non-asymptotic result showing that, with high probability, the KCP procedure retrieves the correct number of change-points, provided that the constant in the penalty is well-chosen; in addition, KCP estimates the change-points locati"},"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":"1612.04740","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-12-14T17:28:17Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"065a2401a390f8a0e1c46ea3374921e031e9efb873204d85557bc8fd59ff5437","abstract_canon_sha256":"5435dc63f45330ebaa9b5e812ce7e7d1ffd792e36f1a41aa95af07b90da12fc4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:41:18.044119Z","signature_b64":"h4LcfZhmi0zBki77yM/MExLnBIidZcYVcHBfo9f46+0NbQ9wwoLxmv4Njd7Q+qSTIBXr0zuMfXk3vkjnOBQpAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f6e053bccae8b804d35d6b705002defc08f361240af1a29a4cb042cb5cc8e904","last_reissued_at":"2026-05-18T00:41:18.043435Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:41:18.043435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Consistent change-point detection with kernels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Damien Garreau, Sylvain Arlot","submitted_at":"2016-12-14T17:28:17Z","abstract_excerpt":"In this paper we study the kernel change-point algorithm (KCP) proposed by Arlot, Celisse and Harchaoui (2012), which aims at locating an unknown number of change-points in the distribution of a sequence of independent data taking values in an arbitrary set. The change-points are selected by model selection with a penalized kernel empirical criterion. We provide a non-asymptotic result showing that, with high probability, the KCP procedure retrieves the correct number of change-points, provided that the constant in the penalty is well-chosen; in addition, KCP estimates the change-points locati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.04740","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":""},"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":"1612.04740","created_at":"2026-05-18T00:41:18.043559+00:00"},{"alias_kind":"arxiv_version","alias_value":"1612.04740v3","created_at":"2026-05-18T00:41:18.043559+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.04740","created_at":"2026-05-18T00:41:18.043559+00:00"},{"alias_kind":"pith_short_12","alias_value":"63QFHPGK5C4A","created_at":"2026-05-18T12:30:01.593930+00:00"},{"alias_kind":"pith_short_16","alias_value":"63QFHPGK5C4AJU25","created_at":"2026-05-18T12:30:01.593930+00:00"},{"alias_kind":"pith_short_8","alias_value":"63QFHPGK","created_at":"2026-05-18T12:30:01.593930+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/63QFHPGK5C4AJU25NNYFAAW67Q","json":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q.json","graph_json":"https://pith.science/api/pith-number/63QFHPGK5C4AJU25NNYFAAW67Q/graph.json","events_json":"https://pith.science/api/pith-number/63QFHPGK5C4AJU25NNYFAAW67Q/events.json","paper":"https://pith.science/paper/63QFHPGK"},"agent_actions":{"view_html":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q","download_json":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q.json","view_paper":"https://pith.science/paper/63QFHPGK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1612.04740&json=true","fetch_graph":"https://pith.science/api/pith-number/63QFHPGK5C4AJU25NNYFAAW67Q/graph.json","fetch_events":"https://pith.science/api/pith-number/63QFHPGK5C4AJU25NNYFAAW67Q/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q/action/timestamp_anchor","attest_storage":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q/action/storage_attestation","attest_author":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q/action/author_attestation","sign_citation":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q/action/citation_signature","submit_replication":"https://pith.science/pith/63QFHPGK5C4AJU25NNYFAAW67Q/action/replication_record"}},"created_at":"2026-05-18T00:41:18.043559+00:00","updated_at":"2026-05-18T00:41:18.043559+00:00"}