Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...
—This paper proposes a method of learning a similarity matrix from pairwise constraints for interactive clustering. The similarity matrix can be learned by solving an optimizatio...
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
We present the derivation of a space efficient parser combinator library: the constructed parsers do not keep unnecessary references to the input, produce online results and effic...
This paper introduces a novel machine learning model called multiple instance ranking (MIRank) that enables ranking to be performed in a multiple instance learning setting. The mo...
Charles Bergeron, Jed Zaretzki, Curt M. Breneman, ...