Sparse matrix problems are di cult to parallelize e ciently on message-passing machines, since they access data through multiple levels of indirection. Inspector executor strategie...
Manuel Ujaldon, Shamik D. Sharma, Joel H. Saltz, E...
We introduce a class of inverse problem estimators computed by mixing adaptively a family of linear estimators corresponding to different priors. Sparse mixing weights are calcula...
Sparse recovery techniques have been shown to produce very accurate acoustic images, significantly outperforming traditional deconvolution approaches. However, so far these propo...
In this paper, we propose a new method for computing and applying language model look-ahead in a dynamic network decoder, exploiting the sparseness of backing-off n-gram language ...
Latent semantic analysis (LSA), as one of the most popular unsupervised dimension reduction tools, has a wide range of applications in text mining and information retrieval. The k...
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G....