{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:NZNR6BOB42WKQEQDM3OV35GVCQ","short_pith_number":"pith:NZNR6BOB","schema_version":"1.0","canonical_sha256":"6e5b1f05c1e6aca8120366dd5df4d5143c455c1e6e6b020a4cb92dfafa398345","source":{"kind":"arxiv","id":"2605.30253","version":1},"attestation_state":"computed","paper":{"title":"Wasserstein Contraction of Coordinate Ascent Variational Inference","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","math.FA","math.OC","math.PR","stat.CO"],"primary_cat":"stat.ML","authors_text":"Adrien Corenflos, Rocco Caprio, Sam Power","submitted_at":"2026-05-28T17:16:22Z","abstract_excerpt":"We study the contraction in Wasserstein distance of the coordinate ascent variational inference algorithm. This is shown to hold under a transport-information inequality at the fixed points and a functional smoothness condition. The results are general and sharp, allow for local convergence guarantees, hold for general smooth manifolds, and also in some non-smooth spaces. We consider applications to Bayesian Gaussian Mixture Models, and high-dimensional Bayesian Probit Regression, and Logistic Regression with P\\'olya-Gamma random variables (i.e. Jaakkola-Jordan's algorithm)."},"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":"2605.30253","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2026-05-28T17:16:22Z","cross_cats_sorted":["cs.LG","math.FA","math.OC","math.PR","stat.CO"],"title_canon_sha256":"8cb525de5f80f42c5954f18897939e559df5b4fff494197feaf39ee085f0be51","abstract_canon_sha256":"438feeda6ad201f6bdc389f3d8d0d3f225459f90f2bb1adfb47e8a7cfcbfa075"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:06:14.105513Z","signature_b64":"Pv7ro8UNKm7W0Jxxu4PONR/ZuptBq+BeskTQBijLGVW6EEAS+PS5gMHG6srrKGJauTbvSrTe+Ugq1tPcMa+3Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e5b1f05c1e6aca8120366dd5df4d5143c455c1e6e6b020a4cb92dfafa398345","last_reissued_at":"2026-05-29T02:06:14.105054Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:06:14.105054Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Wasserstein Contraction of Coordinate Ascent Variational Inference","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","math.FA","math.OC","math.PR","stat.CO"],"primary_cat":"stat.ML","authors_text":"Adrien Corenflos, Rocco Caprio, Sam Power","submitted_at":"2026-05-28T17:16:22Z","abstract_excerpt":"We study the contraction in Wasserstein distance of the coordinate ascent variational inference algorithm. This is shown to hold under a transport-information inequality at the fixed points and a functional smoothness condition. The results are general and sharp, allow for local convergence guarantees, hold for general smooth manifolds, and also in some non-smooth spaces. We consider applications to Bayesian Gaussian Mixture Models, and high-dimensional Bayesian Probit Regression, and Logistic Regression with P\\'olya-Gamma random variables (i.e. Jaakkola-Jordan's algorithm)."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30253","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.30253/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2605.30253","created_at":"2026-05-29T02:06:14.105117+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.30253v1","created_at":"2026-05-29T02:06:14.105117+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30253","created_at":"2026-05-29T02:06:14.105117+00:00"},{"alias_kind":"pith_short_12","alias_value":"NZNR6BOB42WK","created_at":"2026-05-29T02:06:14.105117+00:00"},{"alias_kind":"pith_short_16","alias_value":"NZNR6BOB42WKQEQD","created_at":"2026-05-29T02:06:14.105117+00:00"},{"alias_kind":"pith_short_8","alias_value":"NZNR6BOB","created_at":"2026-05-29T02:06:14.105117+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/NZNR6BOB42WKQEQDM3OV35GVCQ","json":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ.json","graph_json":"https://pith.science/api/pith-number/NZNR6BOB42WKQEQDM3OV35GVCQ/graph.json","events_json":"https://pith.science/api/pith-number/NZNR6BOB42WKQEQDM3OV35GVCQ/events.json","paper":"https://pith.science/paper/NZNR6BOB"},"agent_actions":{"view_html":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ","download_json":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ.json","view_paper":"https://pith.science/paper/NZNR6BOB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.30253&json=true","fetch_graph":"https://pith.science/api/pith-number/NZNR6BOB42WKQEQDM3OV35GVCQ/graph.json","fetch_events":"https://pith.science/api/pith-number/NZNR6BOB42WKQEQDM3OV35GVCQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ/action/storage_attestation","attest_author":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ/action/author_attestation","sign_citation":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ/action/citation_signature","submit_replication":"https://pith.science/pith/NZNR6BOB42WKQEQDM3OV35GVCQ/action/replication_record"}},"created_at":"2026-05-29T02:06:14.105117+00:00","updated_at":"2026-05-29T02:06:14.105117+00:00"}