Anas Barakat

Anas Barakat

Postdoctoral researcher

ETH Zurich

I am an ETH-FDS postdoctoral fellow at ETH Zurich working with Niao He within the Optimization & Decision Intelligence Group in the department of computer science. My research interests include stochastic optimization for machine learning and reinforcement learning.

I obtained my PhD in Applied Mathematics and Computer Science from Institut Polytechnique de Paris at Télécom Paris in the S2A (Signal, Statistics and Learning) team under the supervision of Pascal Bianchi and Walid Hachem. I received my engineering Master’s degree in Applied Mathematics and Computer Science from Télécom Paris and a Master’s degree in Data Science from Université Paris Saclay.

You can find more information about me on my CV.

Interests

  • Stochastic optimization
  • Reinforcement learning

Education

  • PhD in Applied Mathematics and CS, 2021

    Institut Polytechnique de Paris (Télécom Paris)

  • MSc in Data Science (M2), 2018

    Université Paris Saclay

  • MSc in Applied Mathematics and CS, 2018

    Télécom Paris

Research

Anas Barakat, Pascal Bianchi, Julien Lehmann (2022). Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation. In: AISTATS 2022.

Poster Proceedings Arxiv

Anas Barakat (2021). Contributions to non-convex stochastic optimization and reinforcement learning. PhD dissertation.

Slides Thesis

Anas Barakat, Pascal Bianchi, Walid Hachem, Sholom Schechtman (2021). Stochastic optimization with momentum: convergence, fluctuations, and traps avoidance. In: Electronic Journal of Statistics 15 (2), 3892-3947.

DOI Arxiv Journal

Anas Barakat, Pascal Bianchi (2020). Convergence and Dynamical Behavior of the ADAM Algorithm for Non-Convex Stochastic Optimization. In: SIAM Journal on Optimization, 31 (1), 244-274.

Poster Slides Video DOI Arxiv Journal

Anas Barakat, Pascal Bianchi (2019). Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Non-Convex Optimization. In: ACML 2020, PMLR vol.129 p.225-240.

Poster Slides Proceedings Arxiv

Anas Barakat, Pascal Bianchi (2019). Convergence de l'algorithme Adam du point de vue des systèmes dynamiques. In: GRETSI 2019.

PDF Slides

Talks

Invited talk - 14th CMStatistics International Conference
Dec 20, 2021 2:45 PM King’s College, London, United Kingdom (hybrid)
Invited talk - Seminar of the 'Image, Optimization and Probabilities' (IOP) team
Oct 15, 2020 11:00 AM Institut de Mathématiques de Bordeaux
Talk - 2nd Symposium on Machine Learning and Dynamical Systems 2020
Sep 21, 2020 5:40 PM Fields Institute for Research in Mathematical Sciences, Toronto, online
Talk - SMAI MODE days 2020 (Laureate of the Dodu prize)
Sep 7, 2020 3:00 PM Paris-Saclay online
Poster - 11th OPT Workshop on Optimization for Machine Learning 2019
Dec 14, 2019 11:00 AM Vancouver, Canada
See all talks

Reviewing

I have been a referee for:

  • Journals: Journal of Machine Learning Research (JMLR), Journal of Optimization Theory and Applications (JOTA), Systems & Control Letters, Mathematics of Control, Signals, and Systems (MCSS), IEEE Transactions on Image Processing.

  • Conferences: International Conference on Machine Learning (ICML 2022), Conference on Learning Theory (COLT 2022), International Conference on Artificial Intelligence and Statistics (AISTATS 2022, top 10% reviewer).

Teaching

I was a Teaching Assistant at Télécom Paris between 2018 and 2021. I was in particular involved in the following courses (more than 150 hours):

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