We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be expressed as the sum of lower-d...
Continuous probability distributions are widely used to mathematically describe random phenomena in engineering and physical sciences. In this paper, we present a methodology that ...
Mapping composition is a fundamental operation in metadata driven applications. Given a mapping over schemas 1 and 2 and a mapping over schemas 2 and 3, the composition problem is...
Philip A. Bernstein, Todd J. Green, Sergey Melnik,...