Course Syllabus

Course Objective: Modern data mining problems deal with large and complex data sets, and consequently with model containing a large number of parameters. In this course, we will discuss such models (e.g. regression and classification models, graphical models, principal components analysis, matrix completion problems, etc.) and also address estimation and inference issues. In particular, for estimating the model parameter, we will examine in depth key ideas from optimization theory, while we will present basic principles for establishing statistical properties of the resulting estimates. 

For more details see the file course logistics.