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Primal-Dual Optimization Methods for Robust Machine Learning

Institute for Mathematical Sciences via YouTube

Overview

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

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