We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex problem for any log-concave model. ...
Abstract. A theoretical analysis for comparing two linear dimensionality reduction (LDR) techniques, namely Fisher's discriminant (FD) and Loog-Duin (LD) dimensionality reduci...
We propose a new class of stochastic integer programs whose special features are dominance constraints induced by mixed-integer linear recourse. For these models, we establish clo...
Multi-field packet classification is a key enabling function of a variety of network applications, such as firewall processing, Quality of Service differentiation, traffic billing...
This paper reports experiments that explore performance differences in two previous studies that investigated SVM classification of neonatal pain expressions using the Infant COPE ...
Sheryl Brahnam, Chao-Fa Chuang, Frank Y. Shih, Mel...