Optimal Transport for Distributionally Robust Optimization and Applications in Machine Learning
Offered By: VinAI via YouTube
Course Description
Overview
Explore the intersection of Optimal Transport (OT) and Distributionally Robust Optimization (DRO) in this comprehensive seminar. Delve into how OT efficiently morphs probability distributions and how DRO tackles worst-case risk minimization under distributional ambiguity. Discover the computational advantages of OT-based DRO models and their applications in handling distribution shifts and heterogeneous data sources. Learn about the speaker's research in risk analytics and optimization, and gain insights into the role of OT-based DRO in responsible artificial intelligence. Examine how DRO concepts can be applied to solve complex OT problems, providing a holistic view of these interconnected fields in machine learning and decision-making under uncertainty.
Syllabus
Optimal Transport for Distributionally Robust Optimization and Applications in Machine Learning
Taught by
VinAI
Related Courses
Nonconvex Optimization in Matrix Optimization and Distributionally Robust OptimizationInstitute for Pure & Applied Mathematics (IPAM) via YouTube An AI with an Agenda
NDC Conferences via YouTube An AI with an Agenda - How Our Cognitive Biases Leak Into Machine Learning
NDC Conferences via YouTube Building Reliable Machine Learning Systems - Challenges and Approaches
Paul G. Allen School via YouTube Robust Optimization and Generalization
Simons Institute via YouTube