Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
The Internet has solved the age-old problem of network connectivity and thus enabling the potential access to, and data sharing among large numbers of databases. However, enabling ...
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore...
We present novel grid coverage strategies for effective surveillance and target location in distributed sensor networks. We represent the sensor field as a grid (two or three-dimen...
Krishnendu Chakrabarty, S. Sitharama Iyengar, Hair...
We present a variational approachto dense stereo reconstructionwhich combines powerful tools such as regularization and multi-scale processing to estimate directly depth from a num...