We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logica...
Maximum likelihood estimators are often of limited practical use due to the intensive computation they require. We propose a family of alternative estimators that maximize a stoch...
This paper considers a minimum cost flow problem where arc costs are uncertain, and the decision maker wishes to minimize both the expected flow cost and the variance of this co...
: The goal of this paper is to provide computable account for some definite descriptions. To this end, we define in terms of inclusion the notion of distinguishing description and ...
Background: A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed ge...