The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
We propose a local, generative model for similarity-based classification. The method is applicable to the case that only pairwise similarities between samples are available. The c...