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As an application, we propose a practical model for transfer learning based on entropic optimal transport and establish parametric rates of convergence for nonparametric regression and classification.<\/jats:p>","DOI":"10.1214\/24-aos2455","type":"journal-article","created":{"date-parts":[[2025,2,14]],"date-time":"2025-02-14T01:33:06Z","timestamp":1739496786000},"page":"61-90","source":"Crossref","is-referenced-by-count":8,"title":["On the sample complexity of entropic optimal transport"],"prefix":"10.1214","volume":"53","author":[{"given":"Philippe","family":"Rigollet","sequence":"first","affiliation":[{"name":"Department of Mathematics, Massachusetts Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Austin J.","family":"Stromme","sequence":"additional","affiliation":[{"name":"Department of Statistics, ENSAE-CREST"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"108","reference":[{"key":"6","doi-asserted-by":"publisher","unstructured":"Audibert, J.-Y.<\/small> and Tsybakov, A. 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