Bayesian networks (BNs) have been widely used as a model for knowledge representation and probabilistic inferences. However, the single probability representation of conditional d...
For many large systems the computational complexity of complete model-based diagnosis is prohibitive. In this paper we investigate the speedup of the diagnosis process by exploiti...
Inspired by recent theoretical advances in compressive sensing (CS), we propose a new framework that combines the classical local discrete cosine transform used in image compressi...
Jiangtao Wen, Zhuoyuan Chen, Yuxing Han, John D. V...
Motion-compensated temporal wavelet decomposition is a useful framework for fully scalable video compression schemes. In this paper we propose a new approach to reduce the ghostin...
When humans produce summaries of documents, they do not simply extract sentences and concatenate them. Rather, they create new sentences that are grammatical, that cohere with one...