—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Sparse signal representation based on overcomplete dictionaries has recently been extensively investigated, rendering the state-of-the-art results in signal, image and video proce...
Jianzhou Feng, Li Song, Xiaoming Huo, Xiaokang Yan...
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Abstract--With the availability of large corpora of spoken dialog, it is now possible to use data-driven techniques to build and use models of task-oriented dialogs. In this paper,...
Srinivas Bangalore, Giuseppe Di Fabbrizio, Amanda ...
Abstract--An efficient and flexible dictionary structure is proposed for sparse and redundant signal representation. The proposed sparse dictionary is based on a sparsity model of ...