This course presents numerical methods to solve mathematical problems such as systems of linear and nonlinear equations, function approximation, integration and differentiation, and differential equations. ...
Biology is becoming more and more a data science, as illustrated by the explosion of available genome sequences. This course aims to show how we can make sense of such data and harness it in order to understand biological processes in a quantitative way. ...
Students will learn the core concepts and techniques of network analysis with emphasis on causal inference. Theory and
application will be balanced, with students working directly with network data throughout the course. ...
Statistical learning theory for supervised learning and generalization in PAC and online models (VC theory, MDL/SRM, covering numbers, Radamacher Averages, boosting, compression, stability and connection with strong convexity in Banch spaces); Computationa ...