Nicolas Flammarion

INJ 336 (Bâtiment INJ)
Station 14
CH-1015 Lausanne

Administrative data

Teaching & PhD


Computer Science

PhD Programs

Doctoral program in computer and communication sciences


Machine learning

Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented.

Optimization for machine learning

This course teaches an overview of modern optimization methods, for applications in machine learning and data science. In particular, scalability of algorithms to large datasets will be discussed in theory and in implementation.

Fundamental Contents:

  • Convexity, Gradient Methods, Proximal algorithms, Stochastic and Online Variants of mentioned methods, Coordinate Descent Meth

    EECS Seminar: Advanced Topics in Machine Learning

    Students learn about advanced topics in machine learning, artificial intelligence, optimization, and data science. Students also learn to interact with scientific work, analyze and understand strengths and weaknesses of scientific arguments of both theoretical and experimental results.