We give the first representation-independent hardness results for PAC learning intersections of halfspaces, a central concept class in computational learning theory. Our hardness ...
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
Dynamic voltage and frequency scaling has been identified as one of the most effective ways to reduce power dissipation. This paper discusses a compilation strategy that identifies...