{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:EG5RSOY3BQPKSR55X3W5YGR5LO","short_pith_number":"pith:EG5RSOY3","schema_version":"1.0","canonical_sha256":"21bb193b1b0c1ea947bdbeeddc1a3d5b8aa90835a5a810f07f458c3ece20fb62","source":{"kind":"arxiv","id":"1710.08165","version":3},"attestation_state":"computed","paper":{"title":"Fast MCMC sampling algorithms on polytopes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Bin Yu, Martin J. Wainwright, Raaz Dwivedi, Yuansi Chen","submitted_at":"2017-10-23T09:33:02Z","abstract_excerpt":"We propose and analyze two new MCMC sampling algorithms, the Vaidya walk and the John walk, for generating samples from the uniform distribution over a polytope. Both random walks are sampling algorithms derived from interior point methods. The former is based on volumetric-logarithmic barrier introduced by Vaidya whereas the latter uses John's ellipsoids. We show that the Vaidya walk mixes in significantly fewer steps than the logarithmic-barrier based Dikin walk studied in past work. For a polytope in $\\mathbb{R}^d$ defined by $n >d$ linear constraints, we show that the mixing time from a wa"},"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":"1710.08165","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-10-23T09:33:02Z","cross_cats_sorted":[],"title_canon_sha256":"f8a6596a7c2852bf884c9cda5d7dd428e4ddd05255870e4ce636b25ec76ed8f3","abstract_canon_sha256":"e9958daf65ef7289f628cee6a523fe2f3922e2231365a1c9c693777d395ac67a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:59.171162Z","signature_b64":"xdBxuA0j4vzrXrSHu2IAcmes5iqDCnBULQXopldwMnvy5uri+DppwWC/HPc8XIflQXAL97m04y6A6mNiXFaPAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"21bb193b1b0c1ea947bdbeeddc1a3d5b8aa90835a5a810f07f458c3ece20fb62","last_reissued_at":"2026-05-17T23:51:59.170798Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:59.170798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast MCMC sampling algorithms on polytopes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Bin Yu, Martin J. Wainwright, Raaz Dwivedi, Yuansi Chen","submitted_at":"2017-10-23T09:33:02Z","abstract_excerpt":"We propose and analyze two new MCMC sampling algorithms, the Vaidya walk and the John walk, for generating samples from the uniform distribution over a polytope. Both random walks are sampling algorithms derived from interior point methods. The former is based on volumetric-logarithmic barrier introduced by Vaidya whereas the latter uses John's ellipsoids. We show that the Vaidya walk mixes in significantly fewer steps than the logarithmic-barrier based Dikin walk studied in past work. For a polytope in $\\mathbb{R}^d$ defined by $n >d$ linear constraints, we show that the mixing time from a wa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.08165","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":"1710.08165","created_at":"2026-05-17T23:51:59.170858+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.08165v3","created_at":"2026-05-17T23:51:59.170858+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.08165","created_at":"2026-05-17T23:51:59.170858+00:00"},{"alias_kind":"pith_short_12","alias_value":"EG5RSOY3BQPK","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_16","alias_value":"EG5RSOY3BQPKSR55","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_8","alias_value":"EG5RSOY3","created_at":"2026-05-18T12:31:12.930513+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/EG5RSOY3BQPKSR55X3W5YGR5LO","json":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO.json","graph_json":"https://pith.science/api/pith-number/EG5RSOY3BQPKSR55X3W5YGR5LO/graph.json","events_json":"https://pith.science/api/pith-number/EG5RSOY3BQPKSR55X3W5YGR5LO/events.json","paper":"https://pith.science/paper/EG5RSOY3"},"agent_actions":{"view_html":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO","download_json":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO.json","view_paper":"https://pith.science/paper/EG5RSOY3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.08165&json=true","fetch_graph":"https://pith.science/api/pith-number/EG5RSOY3BQPKSR55X3W5YGR5LO/graph.json","fetch_events":"https://pith.science/api/pith-number/EG5RSOY3BQPKSR55X3W5YGR5LO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO/action/storage_attestation","attest_author":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO/action/author_attestation","sign_citation":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO/action/citation_signature","submit_replication":"https://pith.science/pith/EG5RSOY3BQPKSR55X3W5YGR5LO/action/replication_record"}},"created_at":"2026-05-17T23:51:59.170858+00:00","updated_at":"2026-05-17T23:51:59.170858+00:00"}