Program execution speed on modern computers is sensitive, by a factor of two or more, to the order in which instructions are presented to the processor. To realize potential execu...
J. Eliot B. Moss, Paul E. Utgoff, John Cavazos, Do...
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
In this paper we present a general, flexible framework for learning mappings from images to actions by interacting with the environment. The basic idea is to introduce a feature-...