This is a theoretical course about probability in high dimensions. We will look at some mathematical phenomena appearing as the number of random variables grows large - e.g. concentration of measure or universality. ...
The course covers basic econometric models and methods that are routinely applied to obtain inference results in economic and financial applications. ...
This course aims to provide graduate students a thorough grounding in the methods, theory, mathematics and algorithms needed to do research and applications in machine learning. The course covers topics from machine learning, classical statistics, and data ...