Computer Science and Engineering
CSE 290C Advanced Topics in Machine Learning
In-depth study of current research topics in machine learning. Topics vary from year to year but include multi-class learning with boosting and SUM algorithms, belief nets, independent component analysis, MCMC sampling, and advanced clustering methods. Students read and present research papers; theoretical homework in addition to a research project. (Formerly Computer Science 290C.)
Quarter offered
Winter, Spring
Instructor
David Helmbold, Lise Getoor, Xin "Eric" Wang, Cihang Xie