The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
When search techniques are used to solve a practical problem, the solution produced is often brittle in the sense that small execution difficulties can have an arbitrarily large e...
Matthew L. Ginsberg, Andrew J. Parkes, Amitabha Ro...
Probabilistic planning algorithms seek e ective plans for large, stochastic domains. maxplan is a recently developed algorithm that converts a planning problem into an E-Majsat pr...
Although one of the fundamental goals of AI is to understand and develop intelligent systems that have all of the capabilities of humans, there is little active research directly ...
Eye finding is the first step toward building a machine that can recognize social cues, like eye contact and gaze direction, in a natural context. In this paper, we present a real...