—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between p...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
Abstract— We introduce a method for fast and accurate registration of multiple horizontal laser scans obtained by a mobile robot. The method is based on novel representation of t...
— The DPC algorithm developed in our previous work is an efficient way of computing optimal trajectories for multiple robots in a distributed fashion with timeparameterized cons...