"Non UBC"@en . "DSpace"@en . "Wiesemann, Wolfram"@en . "2019-07-14T09:04:04Z"@en . "2019-01-14T16:12"@en . "We provide an exact deterministic reformulation for data-driven chance constrained programs over Wasserstein balls. For individual chance constraints as well as joint chance constraints with right-hand side uncertainty, our reformulation amounts to a mixed-integer conic program. In the special case of a Wasserstein ball with the $1$-norm or the $\infty$-norm, the cone is the nonnegative orthant, and the chance constrained program can be reformulated as a mixed-integer linear program. Using our reformulation, we show that two popular approximation schemes based on the conditional-value-at-risk and the Bonferroni inequality can perform poorly in practice and that these two schemes are generally incomparable with each other."@en . "https://circle.library.ubc.ca/rest/handle/2429/70976?expand=metadata"@en . "41.0 minutes"@en . "video/mp4"@en . ""@en . "Author affiliation: Imperial College London"@en . "10.14288/1.0379829"@en . "eng"@en . "Unreviewed"@en . "Vancouver : University of British Columbia Library"@en . "Banff International Research Station for Mathematical Innovation and Discovery"@en . "Attribution-NonCommercial-NoDerivatives 4.0 International"@en . "http://creativecommons.org/licenses/by-nc-nd/4.0/"@en . "Faculty"@en . "BIRS Workshop Lecture Videos (Banff, Alta)"@en . "Mathematics"@en . "Operations research, mathematical programming"@en . "Computer science"@en . "Applied computer science"@en . "Data-Driven Chance Constrained Programs over Wasserstein Balls"@en . "Moving Image"@en . "http://hdl.handle.net/2429/70976"@en .