We present a practical algorithm that provably achieves the global optimum for a class of bilinear programs commonly arising in computer vision applications. Our approach relies o...
In this paper we use the cumulative distribution of a random variable to define the information content in it and use it to develop a novel measure of information that parallels S...
Coupling the periodic time-invariance of the wavelet transform with the view of thresholding as a projection yields a simple, recursive, wavelet-based technique for denoising sign...
Alyson K. Fletcher, Vivek K. Goyal, Kannan Ramchan...
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...