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Distributed Optimization and Games, 2018-2019

The purpose of this course is to introduce students to large scale machine learning. The focus is as much on optimization algorithms as on distributed systems.

Lessons

You can freely use the slides below for your presentations, but I would like to be informed and please acknowledge the source in your presentation. Any comment is welcome.

Individual project

The individual project is an opportunity for the student to actively use the material taught in the course. The student is free to choose the goal of its project, but is invited to discuss it with the teacher. Possible goals are
  1. reproduce an experimental result in a paper,
  2. design or perform an experiment to support/confute a statement in a paper,
  3. apply some of the optimization algorithms described in the course to a specific problem the student is interested in (e.g. for another course, his/her final project, etc.),
  4. compare different algorithms,
  5. implement an algorithm in a distributed system (Spark, TensorFlow, …),
The mark will take into account: originality of the project, presentation quality, technical correctness, and task difficulty. Any form of plagiarism will lead to reduction of the final mark. A list of possible projects is provided below.

Submission rules

Ideas for possible projects


Exam


Last modified: December 15, 2018