In this paper we investigate a discriminative approach to feature weighting for topic identification using minimum classification error (MCE) training. Our approach learns featu...
When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we prop...
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...
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...