Skolkovo Institute of Science and TechnologyDownload CV
Deep reinforcement learning, low rank decompositions in reinforcement learning with linear value-function approximation and natural language processing.
Current activities in the Laboratory
Multi-agent exploration of reinforcement learning environments based on maximization of feature matrix volume.
Benefits of treating deep reinforcement learning as linear Q-function approximation with non-linear feature encoder.
Publications since 2016