Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
: In this paper, we study the parameter estimation problem in a general heteroscedastic linear system, by putting the problem in the framework of the bilinear approach to low-rank ...
We review current methods for evaluating models in the cognitive sciences, including theoretically-based approaches, such as Bayes Factors and MDL measures, simulation approaches,...
Richard M. Shiffrin, Michael D. Lee, Woojae Kim, E...
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Timing exception verification has become a center of interest as incorrect constraints can lead to chip failures. Proving that a false path is valid or not is a difficult problem ...