Services for locating mobile objects are often organized as a distributed search tree. The advantage of such an organization is that the service can easily scale as a distributed ...
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 a...
Successful self-regulated learning in a personalized learning environment (PLE) requires self-monitoring of the learner and reflection of learning behaviour. We introduce a tool ca...
Hans-Christian Schmitz, Maren Scheffel, Martin Fri...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...