A framework for the regularized estimation of nonuniform dimensionality and density in high dimensional data is introduced in this work. This leads to learning stratifications, th...
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
This paper describes an algorithm for generating compact 3D models of indoor environments with mobile robots. Our algorithm employs the expectation maximization algorithm to fit a...
Hand-coded vision systems are problematic in complex medical domains and are hard to change as new information emerges. Knowledge-Engineering and Machine Learning approaches to in...
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...