Although modern control theories have been successfully applied to solve a variety of problems, they are often mathematically and physically too specific to describe and analyze t...
To perform automatic, unconscious inference, the human brain must solve the "binding problem" by correctly grouping properties with objects. Temporal binding models like...
We combine a "hybrid" force/position control scheme with a potential field approach into a novel method for collision recovery and navigation in unknown environments. It...
We define notions of stability for learning algorithms and show how to use these notions to derive generalization error bounds based on the empirical error and the leave-one-out e...
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...