Primal-Dual Optimization Methods for Robust Machine Learning
Institute for Mathematical Sciences via YouTube
Overview
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Explore primal-dual optimization methods for robust machine learning in this 47-minute lecture by Stephen Wright from the University of Wisconsin-Madison. Delve into advanced techniques that enhance the resilience and reliability of machine learning models. Gain insights into the application of primal-dual algorithms in addressing challenges related to robustness in various machine learning scenarios. Learn how these optimization methods can improve model performance and stability across different domains.
Syllabus
Primal-dual Optimization Methods for Robust Machine Learning
Taught by
Institute for Mathematical Sciences