SPEAKER

Nonsmooth optimization models and methods in machine learning

Abstract. Unsupervised learning, semi-supervised learning, supervised learning, regression analysis and clusterwise regression analysis problems are among most important problems in machine learning. There are various optimization models of these problems. Nonsmooth optimization approaches lead to better models with significantly less decision variables than those based on other optimization approaches. In this talk, we discuss nonsmooth optimization models of various machine learning problems as well as numerical methods for solving nonsmooth optimization problems in these models.