We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
We propose Compact And Real-time Descriptors (CARD) which can be computed very rapidly and be expressed by short binary codes. An efficient algorithm based on lookup tables is pr...
In this study, we propose two algorithms for measuring the distance between shape boundaries. In the algorithms, shape boundary is represented by the Beam Angle Statistics (BAS), w...
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...