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Furthermore, our DRO framework can be conveniently used to address data-driven decision-making problems under contaminated samples. Finally, the theoretical results are illustrated using a single-item newsvendor problem and a portfolio allocation problem with side information.<\/jats:p>","DOI":"10.1007\/s10107-021-01724-0","type":"journal-article","created":{"date-parts":[[2021,11,22]],"date-time":"2021-11-22T10:02:57Z","timestamp":1637575377000},"page":"1069-1105","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Distributionally robust stochastic programs with side information based on trimmings"],"prefix":"10.1007","volume":"195","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0124-8772","authenticated-orcid":false,"given":"Adri\u00e1n","family":"Esteban-P\u00e9rez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9114-686X","authenticated-orcid":false,"given":"Juan M.","family":"Morales","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,11,22]]},"reference":[{"key":"1724_CR1","unstructured":"Agull\u00f3 Antol\u00edn, M.: Trimming methods for model validation and supervised classification in the presence of contamination. 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