Query-oriented summarization aims at extracting an informative summary from a document collection for a given query. It is very useful to help users grasp the main information rel...
We propose a new transform coding algorithm that integrates all optimization steps into a coherent and consistent framework. Each iteration of the algorithm is designed to minimiz...
We propose a novel framework to build descriptors of local intensity that are invariant to general deformations. In this framework, an image is embedded as a 2D surface in 3D spac...
Pseudo-relevance feedback has proven to be an effective strategy for improving retrieval accuracy in all retrieval models. However the performance of existing pseudo feedback meth...
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...