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Daniel Kuhn is a full professor and chair of risk analytics and optimization at EPFL, where he conducts research on data-driven optimization, stochastic programming and robust optimization. He has published several papers on these topics in journals such as Mathematical Programming, SIAM Journal on Optimization and Operations Research.
Daniel Kuhn. Professor of Operations Research. Verified email at epfl.ch - Homepage. stochastic programming robust optimization data-driven optimization. Articles 1–20.
Daniel Kuhn is Professor of Operations Research at the College of Management of Technology at EPFL, where he holds the Chair of Risk Analytics and Optimization (RAO).
Aug 23, 2019 · Daniel Kuhn and co-authors present a tutorial on Wasserstein distributionally robust optimization, a data-driven decision-making approach that performs well under the most adverse distribution. The paper covers theory, applications and computational benefits of this method in machine learning.
- Daniel Kuhn, Peyman Mohajerin Esfahani, Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh
- 2019
Jun 11, 2024 · Daniel Kuhn gave a plenary talk at the VOCAL Optimization Conference. 11.06.24 — The VOCAL conference focuses on recent advances in continuous as well as discrete optimization, complexity and convergence theory, high performance optimization software and novel applications of optimization.
Daniel Kuhn: Data-driven and Distributionally Robust Optimization and Applications -- Part 1/2. Speaker: Daniel Kuhn (EPFL)Event: DTU CEE Summer School 2018 on "Modern Optimization in...
- 78 min
- 14.9K
- DTU: Lectures on Power & Energy Systems
Daniel Kuhn's 132 research works with 6,681 citations and 11,216 reads, including: A Unified Theory of Robust and Distributionally Robust Optimization via the...
