We present a novel approach to the problem of the indoor localization in wireless environments. The main contribution of this paper is four folds: (a) We show that, by projecting t...
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
Live migration of virtual hard disks between storage arrays has long been possible. However, there is a dearth of online tools to perform automated virtual disk placement and IO l...
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...