Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
In this paper, we present an algorithm to propagate an n-ary constraint (with n greater than 2) specifying the relative positions of points in a three-dimensional rigid group. The ...
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
The data stream captured by recording inhabitantdevice interactions in an environment can be mined to discover significant patterns, which an intelligent agent could use to automa...
Matrix factorization algorithms are frequently used in the machine learning community to find low dimensional representations of data. We introduce a novel generative Bayesian pro...