Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
The new market forces have affected the operation of distribution centers (DCs) extremely. The DCs demand an increased productivity and a low cost in their daily operation. This pa...
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
In this paper, we present a variational Bayes (VB) approach for image segmentation. First, image is modeled by a mixture model, and then with the techniques of factor analyzer, th...
Zhenglong Li, Qingshan Liu, Jian Cheng, Hanqing Lu