3rd year of study
Approved topic of thesis: Application of Bayesian methods for meta-reinforcement learning
Academic Supervisor: Ветров Дмитрий Петрович
Student Term / Thesis Papers
V. Kalashnykov, Reinforcement Learning for Geometry Problems. Faculty of Computer Science, 2020
A. Fritsler, Program for Prediction of Partially Observable Process Dynamics. Faculty of Computer Science, 2019
M. Konobeev, Distributional and Entropy-Regularized Reinforcement Learning. Faculty of Computer Science, 2018
A. Klimkin, Goal-Based Reinforcement Learning via Experts Hints. Faculty of Computer Science, 2018
E. Vakhrameeva, Deep Exploration in Reinforcement Learning. Faculty of Computer Science, 2018
- Chapter Кузнецов А. С., Shvechikov P., Grishin A., Vetrov D. Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics, in: International Conference on Machine Learning (ICML 2020). PMLR, 2020.
- Book Кузнецов А. С., Shvechikov P., Grishin A., Vetrov D. International Conference on Machine Learning (ICML 2020). PMLR, 2020.
HSE master’s programme alumni and an HSE doctoral student received an international Catalyst Grant from Digital Science in support of the development of their startup, MLprior, a service for researchers and scientists. HSE News Service spoke with Vladislav Ishimtsev, one of the startup creators, about the biggest ‘thorns’ in researchers’ sides, artificial intelligence, and the possibility of a machine uprising.
From late March and early April, HSE will offer four new coursers on Coursera on intercultural communication, machine learning, computer vision, and stochastic processes.