We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Fost...
Abstract. Most common feature selection techniques for document categorization are supervised and require lots of training data in order to accurately capture the descriptive and d...
Background: Single Nucleotide Polymorphisms (SNPs) are the most common type of polymorphisms found in the human genome. Effective genetic association studies require the identific...
Given the spectral difference between speech and acoustic events, we propose using Kullback-Leibler distance to quantify the discriminant capability of all speech feature componen...
Xi Zhou, Xiaodan Zhuang, Ming Liu, Hao Tang, Mark ...
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...