Multilingual parallel text corpora provide a powerful means for propagating linguistic knowledge across languages. We present a model which jointly learns linguistic structure for...
As the competition becomes more and more intense, many retail small store chain operators are eager to know how to evaluate new store locations quantitatively to support a scienti...
Building cost estimation models is often considered a search problem in which the solver should return an optimal solution satisfying an objective function. This solution also nee...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...