Aymeric Dieuleveut
Researcher
Computer Science Department
Ecole Normale Superieure (ENS)
France
Biography
I am a third year Ph.D. student in the Sierra Team, which is part of the DI/ENS (Computer Science Department of École Normale Supérieure). I graduated from Ecole Normale Supérieure de Paris (Ulm) in 2014 and got a Masters Degree in Mathematics, Probability and Statistics (at Université Paris-Sud, Orsay). I am supervised by Francis Bach. My main research interests are statistics, optimization, stochastic approximation, high-dimensional learning, non-parametric statistics, scalable kernel methods. From March to August 2016, I was a visiting scholar researcher at University of California Berkeley, under the supervision of Martin Wainwright.
Research Interest
My main research interests are statistics, optimization, stochastic approximation, high-dimensional learning, non-parametric statistics, scalable kernel methods.
Publications
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Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains Aymeric Dieuleveut, Alain Durmus and Francis Bach arXiv:1707.06386 [math.ST].
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Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression Aymeric Dieuleveut, Nicolas Flammarion and Francis Bach To appear in Journal of Machine Learning Research (JMLR), arXiv:1602.05419 [math.ST].
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Non-parametric Stochastic Approximation with Large Step sizes Aymeric Dieuleveut and Francis Bach. Published in the Annals of Statistics.
