There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
In this paper, we discuss how to apply the rate distortion technique to select the optimal mode in the scalable coding. Firstly, we analyze this problem from a general scalable mo...
Optical diffusion tomography attempts to reconstruct an object cross section from measurements of scattered and attenuated light. While Bayesian approaches are well suited to this...
Jong Chul Ye, Charles A. Bouman, Rick P. Millane, ...
In statistical machine translation, a researcher seeks to determine whether some innovation (e.g., a new feature, model, or inference algorithm) improves translation quality in co...
Jonathan H. Clark, Chris Dyer, Alon Lavie, Noah A....
Sparse representations using overcomplete dictionaries are used in a variety of field such as pattern recognition and compression. However, the size of dictionary is usually a tra...