Martin Jaggi
martin.jaggi@epfl.ch +41 21 693 70 59 http://mlo.epfl.ch
Group Webpage:
EPFL IC IINFCOM MLO
INJ 341 (Bâtiment INJ)
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CH-1015 Lausanne
41 21 693 70 59
41 21 693 52 26
Office: INJ 341
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Fields of expertise
Teaching & PhD
Teaching
Computer Science
Communication Systems
PhD Programs
PhD Students
Cordonnier Jean-Baptiste Francis Marie Juliette, Gupta Prakhar, He Lie, Karimi Mahabadi Rabeeh, Karimireddy Sai Praneeth Reddy, Koloskova Anastasiia, Lin Tao, Pagliardini Matteo, Vogels Thijs,Past EPFL PhD Students
Drumond Lages De Oliveira Mario Paulo ,Courses
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
Topics in Machine Learning Systems
This course will cover the latest technologies, platforms and research contributions in the area of machine learning systems. The students will read, review and present papers from recent venues across the systems for ML spectrum.
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.