Talks

To scale Gaussian processes (GPs) to large data sets we introduce the robust Bayesian Committee Machine (rBCM), a practical and …

Autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a …

Autonomous learning has been a promising direction in control and robotics for more than a decade since learning models and controllers …

In this paper, we introduce PILCO, a practical, data-efficient model-based policy search method. PILCO reduces model bias, one of the …

We propose an analytic moment-based filter for nonlinear stochastic dynamical systems modeled by Gaussian processes. Exact expressions …