Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
This paper extends the kinematic manipulability concept commonly used for serial manipulators to general constrained rigid multibody systems. Examples of such systems include multi...
Abstract. Optimistic execution techniques are widely used in the field of parallel discrete event simulation. In this paper we discuss the use of optimism as a technique for paral...
Time is a crucial variable in planning and often requires special attention since it introduces a specific structure along with additional complexity, especially in the case of dec...
We present an efficient generalization of the sparse pseudo-input Gaussian process (SPGP) model developed by Snelson and Ghahramani [1], applying it to binary classification pro...