An unsupervised probabilistic learning framework for normalizing product records across different retailer Web sites is presented. Our framework decomposes the problem into two ta...
Abstract. Branch predictors are associated with critical design issues for nowadays instruction greedy processors. We study two important domains where the optimization of decision...
Patrick Carribault, Christophe Lemuet, Jean-Thomas...
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Classification problems with a very large or unbounded set of output categories are common in many areas such as natural language and image processing. In order to improve accurac...
Ivan Titov, Alexandre Klementiev, Kevin Small, Dan...
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales