AI Seminar: Recent Applications of Stein’s Method in Machine Learning
Qiang Liu, Department of Computer Science
University of Texas at Austin
As a fundamental technique for approximating and bounding distances between probability measures, Stein’s method has caught the attention in the machine learning community recently; some of the key ideas in Stein’s method have been leveraged and extended for developing practical and efficient computational methods for learning and using large scale, intractable probabilistic models.