{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:U7XEXPAFQXVN434DBBDNVMGOPG","short_pith_number":"pith:U7XEXPAF","schema_version":"1.0","canonical_sha256":"a7ee4bbc0585eade6f830846dab0ce79801b14a76ad05b5f251a46b43e7916ef","source":{"kind":"arxiv","id":"1704.02054","version":3},"attestation_state":"computed","paper":{"title":"Optimal Las Vegas Locality Sensitive Data Structures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Thomas Dybdahl Ahle","submitted_at":"2017-04-06T23:44:31Z","abstract_excerpt":"We show that approximate similarity (near neighbour) search can be solved in high dimensions with performance matching state of the art (data independent) Locality Sensitive Hashing, but with a guarantee of no false negatives.\n  Specifically, we give two data structures for common problems.\n  For $c$-approximate near neighbour in Hamming space we get query time $dn^{1/c+o(1)}$ and space $dn^{1+1/c+o(1)}$ matching that of \\cite{indyk1998approximate} and answering a long standing open question from~\\cite{indyk2000dimensionality} and~\\cite{pagh2016locality} in the affirmative.\n  By means of a new"},"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":"1704.02054","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2017-04-06T23:44:31Z","cross_cats_sorted":[],"title_canon_sha256":"97587f3d60ab7951b6a4b878795250b76a9f7a00c1f2707c9260422000defa6a","abstract_canon_sha256":"cb1dc2c0027660a53fb3835a4592f15d9dd360bb34715e2ee2704becd6b262be"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:12:14.334187Z","signature_b64":"KqV22AtKeFh93F1suL3UffBnH06U4nQ5uusN1uKaejkuLdYhuanHRNMjOQhvvBrQmU5wjZlDeU9cs2mOXY9uDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7ee4bbc0585eade6f830846dab0ce79801b14a76ad05b5f251a46b43e7916ef","last_reissued_at":"2026-05-18T00:12:14.333715Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:12:14.333715Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimal Las Vegas Locality Sensitive Data Structures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Thomas Dybdahl Ahle","submitted_at":"2017-04-06T23:44:31Z","abstract_excerpt":"We show that approximate similarity (near neighbour) search can be solved in high dimensions with performance matching state of the art (data independent) Locality Sensitive Hashing, but with a guarantee of no false negatives.\n  Specifically, we give two data structures for common problems.\n  For $c$-approximate near neighbour in Hamming space we get query time $dn^{1/c+o(1)}$ and space $dn^{1+1/c+o(1)}$ matching that of \\cite{indyk1998approximate} and answering a long standing open question from~\\cite{indyk2000dimensionality} and~\\cite{pagh2016locality} in the affirmative.\n  By means of a new"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.02054","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":"1704.02054","created_at":"2026-05-18T00:12:14.333798+00:00"},{"alias_kind":"arxiv_version","alias_value":"1704.02054v3","created_at":"2026-05-18T00:12:14.333798+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.02054","created_at":"2026-05-18T00:12:14.333798+00:00"},{"alias_kind":"pith_short_12","alias_value":"U7XEXPAFQXVN","created_at":"2026-05-18T12:31:46.661854+00:00"},{"alias_kind":"pith_short_16","alias_value":"U7XEXPAFQXVN434D","created_at":"2026-05-18T12:31:46.661854+00:00"},{"alias_kind":"pith_short_8","alias_value":"U7XEXPAF","created_at":"2026-05-18T12:31:46.661854+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/U7XEXPAFQXVN434DBBDNVMGOPG","json":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG.json","graph_json":"https://pith.science/api/pith-number/U7XEXPAFQXVN434DBBDNVMGOPG/graph.json","events_json":"https://pith.science/api/pith-number/U7XEXPAFQXVN434DBBDNVMGOPG/events.json","paper":"https://pith.science/paper/U7XEXPAF"},"agent_actions":{"view_html":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG","download_json":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG.json","view_paper":"https://pith.science/paper/U7XEXPAF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1704.02054&json=true","fetch_graph":"https://pith.science/api/pith-number/U7XEXPAFQXVN434DBBDNVMGOPG/graph.json","fetch_events":"https://pith.science/api/pith-number/U7XEXPAFQXVN434DBBDNVMGOPG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG/action/storage_attestation","attest_author":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG/action/author_attestation","sign_citation":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG/action/citation_signature","submit_replication":"https://pith.science/pith/U7XEXPAFQXVN434DBBDNVMGOPG/action/replication_record"}},"created_at":"2026-05-18T00:12:14.333798+00:00","updated_at":"2026-05-18T00:12:14.333798+00:00"}