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Machine Learning for Optimal Power Flows
...Optimal power flow is a cornerstone of electrical power system operations: it is...

Statistical Analysis of Wasserstein Distributionally Robust Estimators
...We consider statistical methods which invoke a min-max distributionally robust ...

Exactness in SDP Relaxations of QCQPs: Theory and Applications
...Quadratically constrained quadratic programs (QCQPs) are a fundamental class of ...

Storytelling with Sports Analytics
...As the use of analytics grows in the sports industry, debates about the ...

New Audio Available for Media Use: What is Interpretable Machine Learning?
...BALTIMORE, MD, April 25, 2022 ��� New audio is available for media use featuring...

Discrete Choice Models and Applications in Operations Management
...Modeling decision behavior among multiple choices has been an active research ...

Game Theory and the COVID-19 Pandemic
...The world is now faced with the COVID-19 pandemic, a healthcare disaster, not ...

Surrogate-based Simulation Optimization
...Simulation models are widely used in practice to facilitate decision-making in a...

Good and Bad Optimization Models: Insights from Rockafellians
...A basic requirement for a mathematical model is often that its solution (output...

Ethics in Data Collection and Management
...BALTIMORE, MD, April 28, 2022 ��� New audio is available for media use featuring...