The Seminar is organized every first Tuesday of the month with 2 presentations followed by a small refreshment. The localization of the seminar will change to accommodate the different labs.
Due to access restriction, you need to register for the seminar. A link is provided in the description and should also be sent with the seminar announcement. It will also help us organize for the food quantities. If you think you will come, please register! (even if you are unsure)
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Joon Kwon-Unifying mirror descent and dual averaging
We introduce and analyse a new family of algorithms which generalizes and unifies both the mirror descent and the dual averaging algorithms. In the framework of this family, we define a new algorithm for constrained optimization with the aim of combining the advantages of mirror descent and dual averaging. In practice, this new algorithm converges as fast as mirror descent and dual averaging, and in some situations greatly outperforms them. Besides, we demonstrate how our algorithms can also be applied to solving variational inequalities. This is joint work with Anatoli Juditsky and Eric Moulines.
The goal of this talk is to introduce the audience to the problem of algorithmic fairness. I will provide a general overview on the topic, describe various available notions of fairness in classification and regression, and present main approaches to tackle this problem. I will also present some recent theoretical results both in classification and regression. This talk is based on joint works with C. Denis, M. Hebiri, L. Oneto, and M. Pontil.