In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
The problem of writing high performance parallel applications becomes even more challenging when irregular, sparse or adaptive methods are employed. In this paper we introduce com...
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
This study focuses on determining a procedure to select effective negative examples for development of improved Support Vector Machine (SVM) based speaker recognition. Selection o...
Jun-Won Suh, Yun Lei, Wooil Kim, John H. L. Hansen
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...