Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
We perform a systematic evaluation of feature selection (FS) methods for support vector machines (SVMs) using simulated high-dimensional data (up to 5000 dimensions). Several findi...
Abstract. Most classification methods assume that the samples are drawn independently and identically from an unknown data generating distribution, yet this assumption is violated ...
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...