In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Alloy specifications are used to define lightweight models of systems. We present Alchemy, which compiles Alloy specifications into implementations that execute against persistent...
Shriram Krishnamurthi, Kathi Fisler, Daniel J. Dou...
We propose a method for estimating the credibility of the posted information from users. The system displays these information on the map. Since posted information can include sub...
Koji Yamamoto, Daisuke Katagami, Katsumi Nitta, Ak...
We present a unified view of many translation algorithms that synthesizes work on deductive parsing, semiring parsing, and efficient approximate search algorithms. This gives rise...