The Dao of Robustness
We present a general framework for data-driven optimization called robustness optimization that favors solutions for which a risk-aware objective function would best attain an acceptable target even when the actual […]
We present a general framework for data-driven optimization called robustness optimization that favors solutions for which a risk-aware objective function would best attain an acceptable target even when the actual […]
Dr. Ying Chen is a financial statistician and data scientist. She develops statistical modelling and machine learning methods customized for nonstationary, high frequency and large dimensional complex data such as […]
James Zou is an assistant professor of biomedical data science, CS and EE at Stanford University. He is also a Chan-Zuckerberg investigator. James work on making ML more reliable, accountable […]
A/P Christopher Thomas Ryan teaches at the University of British Columbia in the Sauder School of Business. His research interests include optimization (broadly defined), theoretical economics, operations management, organizational learning, […]
Ilya O. Ryzhov is an Associate Professor of Operations Management and Management Science at the Robert H. Smith School of Business, University of Maryland. His research focuses on decision-making under […]
