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Separable Dictionary Learning     Separable  Dictionary  Learning       2013/5/2
Many techniques in computer vision, machine learning, and statistics rely on the fact that a signal of interest admits a sparse representation over some dictionary. Dictionaries are either available a...
This article addresses the issue of representing electroencephalographic (EEG) signals in an efficient way. While classical approaches use a fixed Gabor dictionary to analyze EEG signals, this article...
We present a two-stage approach for learning dic-tionaries for object classification tasks based on the principle of information maximization. The proposed method seeks a dictionary that is compact, d...
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the cont...
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the cont...

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