Talks and lectures by guests and members of HDI Lab (in English)
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- Talk by Alexey Naumov (HSE University), Posterior sampling and Bayesian bootstrap: sample complexity and regret bounds (1), Fall into ML 2022) , 01-03 ноября 2022 г.
- Talk by Daniil Tiapkin (HSE University), Posterior sampling and Bayesian bootstrap: sample complexity and regret bounds (2), Fall into ML 2022) , 01-03 ноября 2022 г.
- Talk by Sergey Samsonov (HSE University), Local-Global MCMC kernels: the best of both worlds, Fall into ML 2022) , 01-03 ноября 2022 г.
- Talk by Dmitrii Ostrovskii (University of Southern California), Near-Optimal Model Discrimination with Non-Disclosure, June 22, 2021
- Talk "MCMC, Langevin diffusion, and control variates for MCMC" by Eric Moulines (École Polytechnique, HSE University, ENS Paris-Saclay) at the Conference "Theory of Probability and its Applications: P.L. Chebyshev - 200", May 20, 2021
- Talk by Quentin Paris (HSE University), Online learning with exponential weights in metric spaces, April 20, 2021
- Talk by Dmytro Perekrestenko (ETH Zurich), Constructive Universal High-Dimensional Distribution Generation through Deep ReLU, March 30, 2021
- Talk by Maxim Panov (Skoltech), Stochastic normalizing flows, March 23, 2021
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- Talk by Nikita Puchkin (HSE University, IITP), Rates of convergence for density estimation with GANs, February 9, 2021
- Talk by Michel Ledoux (Université de Toulouse, France) "On Optimal Matching of Random Samples", September 17, 2019.
- Mini-course by Eric Moulines (Ecole Polytechnique (Paris), HSE University) “Introduction to reinforcement learning”, April 16 and 23, 2019.
Lecture №1:Lecture №2:
- Mini-course by Sergey Bobkov (University of Minnesota, HSE University) “Strong probability distances and limit theorems”, May 17 and 24, 2018.
Lecture №1:
Lecture №2: - Talk by Eric Moulines (Ecole Polytechnique (Paris), HSE University) Perturbed Proximal Gradient Algorithms at the Faculty of Computer Science , February 22, 2018.
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