{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:KUSMPV5ATCSPOFOZPHAM6YN5AP","short_pith_number":"pith:KUSMPV5A","schema_version":"1.0","canonical_sha256":"5524c7d7a098a4f715d979c0cf61bd03ee9d90049bae8e0b88b83e81bfc73fff","source":{"kind":"arxiv","id":"1611.03579","version":1},"attestation_state":"computed","paper":{"title":"Collision-based Testers are Optimal for Uniformity and Closeness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT","math.ST","stat.TH"],"primary_cat":"cs.DS","authors_text":"Eric Price, Ilias Diakonikolas, John Peebles, Themis Gouleakis","submitted_at":"2016-11-11T03:59:24Z","abstract_excerpt":"We study the fundamental problems of (i) uniformity testing of a discrete distribution, and (ii) closeness testing between two discrete distributions with bounded $\\ell_2$-norm. These problems have been extensively studied in distribution testing and sample-optimal estimators are known for them~\\cite{Paninski:08, CDVV14, VV14, DKN:15}.\n  In this work, we show that the original collision-based testers proposed for these problems ~\\cite{GRdist:00, BFR+:00} are sample-optimal, up to constant factors. Previous analyses showed sample complexity upper bounds for these testers that are optimal as a f"},"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":"1611.03579","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2016-11-11T03:59:24Z","cross_cats_sorted":["cs.IT","cs.LG","math.IT","math.ST","stat.TH"],"title_canon_sha256":"57548ae3bb2edd635ecba10fc478365cbce5d501cb8b4b44fd897f6e9990bd5d","abstract_canon_sha256":"f3666c618da5939022039541ca2c86dee202df89263ce2cbf7281956004fbec7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:59:33.822134Z","signature_b64":"sGXZOV0fHr2vSqXtekdT2uBiGxpvRwJJdYFzSlNNGybApIObX+YISYG06cW2QcixQIkvc3ZCpEgjxRLtNnMqCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5524c7d7a098a4f715d979c0cf61bd03ee9d90049bae8e0b88b83e81bfc73fff","last_reissued_at":"2026-05-18T00:59:33.821439Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:59:33.821439Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Collision-based Testers are Optimal for Uniformity and Closeness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT","math.ST","stat.TH"],"primary_cat":"cs.DS","authors_text":"Eric Price, Ilias Diakonikolas, John Peebles, Themis Gouleakis","submitted_at":"2016-11-11T03:59:24Z","abstract_excerpt":"We study the fundamental problems of (i) uniformity testing of a discrete distribution, and (ii) closeness testing between two discrete distributions with bounded $\\ell_2$-norm. These problems have been extensively studied in distribution testing and sample-optimal estimators are known for them~\\cite{Paninski:08, CDVV14, VV14, DKN:15}.\n  In this work, we show that the original collision-based testers proposed for these problems ~\\cite{GRdist:00, BFR+:00} are sample-optimal, up to constant factors. Previous analyses showed sample complexity upper bounds for these testers that are optimal as a f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.03579","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":"1611.03579","created_at":"2026-05-18T00:59:33.821556+00:00"},{"alias_kind":"arxiv_version","alias_value":"1611.03579v1","created_at":"2026-05-18T00:59:33.821556+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.03579","created_at":"2026-05-18T00:59:33.821556+00:00"},{"alias_kind":"pith_short_12","alias_value":"KUSMPV5ATCSP","created_at":"2026-05-18T12:30:29.479603+00:00"},{"alias_kind":"pith_short_16","alias_value":"KUSMPV5ATCSPOFOZ","created_at":"2026-05-18T12:30:29.479603+00:00"},{"alias_kind":"pith_short_8","alias_value":"KUSMPV5A","created_at":"2026-05-18T12:30:29.479603+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/KUSMPV5ATCSPOFOZPHAM6YN5AP","json":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP.json","graph_json":"https://pith.science/api/pith-number/KUSMPV5ATCSPOFOZPHAM6YN5AP/graph.json","events_json":"https://pith.science/api/pith-number/KUSMPV5ATCSPOFOZPHAM6YN5AP/events.json","paper":"https://pith.science/paper/KUSMPV5A"},"agent_actions":{"view_html":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP","download_json":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP.json","view_paper":"https://pith.science/paper/KUSMPV5A","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1611.03579&json=true","fetch_graph":"https://pith.science/api/pith-number/KUSMPV5ATCSPOFOZPHAM6YN5AP/graph.json","fetch_events":"https://pith.science/api/pith-number/KUSMPV5ATCSPOFOZPHAM6YN5AP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP/action/storage_attestation","attest_author":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP/action/author_attestation","sign_citation":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP/action/citation_signature","submit_replication":"https://pith.science/pith/KUSMPV5ATCSPOFOZPHAM6YN5AP/action/replication_record"}},"created_at":"2026-05-18T00:59:33.821556+00:00","updated_at":"2026-05-18T00:59:33.821556+00:00"}