The high computational cost of nonlinear support vector machines has limited their usability for large-scale problems. We propose two novel stochastic algorithms to tackle this pr...
In recent years, metric learning in the semisupervised setting has aroused a lot of research interests. One type of semi-supervised metric learning utilizes supervisory informatio...
There have been research initiatives in centralized control recently, which advocate that the control of an autonomous system (AS) should be performed in a centralized fashion. In ...
Non-negative matrix factorization (NMF) is a powerful feature extraction method for finding parts-based, linear representations of non-negative data . Inherently, it is unsupervis...
This paper addresses the optimal rate allocation problem in overlay content distribution for efficient utilization of limited bandwidths. We systematically present a series of opti...