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Frauke Liers - (Data-driven) distributional robustness over time: How to 'learn' relevant uncertai..
Daniel Kuhn - Wasserstein Distributionally Robust Optimization with Heterogeneous Data Sources
Finding Flexibility in Data Center Use, with Johanna Mathieu
From Moderate Deviations Theory to Distributionally Robust Optimization: Correlated Data
Earth Day Teach Out | Prof. Johanna Mathieu on a Sustainable Power Grid
Johanna Mathieu: Harnessing Residential Loads for Demand Response
RIFT - Robust Intervention & Future Testing
Lightning Talk: Johanna Mathieu
Lightning Talk: Johanna Mathieu
IROS2020 Data-Driven Distributionally Robust Electric Vehicle Balancing under Model Uncertainties
Data-driven distributionally robust optimization with MOSEK
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Last Updated: September 30, 2026
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The water and power networks are heavily interdependent. The water network requires power for the extraction, treatment, and ... Speaker: Daniel Kuhn (EPFL) Event: DTU CEE Summer School 2018 on "Modern Please find more details about the seminar on our webpage: sites.google.com/view/row-series/home. More information on our webpage: sites.google.com/view/row-series/home. In this week's episode, host Kristin Hayes is joined by University of Michigan Associate Professor Full title: From Moderate Deviations Theory to Presented December 8, 2012 at the University of Florida by the Laboratory for Cognition and Control in Complex Systems. As part of the Lightning Talk Series focused on Cities, Mobility, and the Built Environment, Publication Title: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Article Title: This video introduces the viewer to the work presented in the award winning paper titled "
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