Volkan Cevher

ELE 233 (Bâtiment ELE)
Station 11
1015 Lausanne

Web site:  Web site:  https://lions.epfl.ch

Web site:  Web site:  https://cce.epfl.ch/

Administrative data

Fields of expertise

Machine Learning 
Reinforcement Learning
Deep learning


Infoscience publications

Teaching & PhD


Electrical and Electronics Engineering


Mathematics of data: from theory to computation

This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees, describe scalable solution techniques and algorithms, and illustrate the trade-offs involved.

Reinforcement learning

This course describes theory and methods for Reinforcement Learning (RL), which revolves around decision making under uncertainty. The course covers classic algorithms in RL as well as recent algorithms under the lens of contemporary optimization.

Online learning in games

This course provides an overview of recent developments in online learning, game theory, and variational inequalities and their point of intersection with a focus on algorithmic development. The primary approach is to lay out the different problem classes and their associated optimal rates.

Multi Agent Reinforcement Learning

The goal of the summer school are providing a rigorous introduction to the foundations of MARL and highlight the challenges that arise in the modern research directions in this area.

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.