Xiyang Dai

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Sparse representations have been successfully applied to signal processing, computer vision and machine learning. Currently there is a trend to learn sparse models directly on structure data, such as region covariance. However , such methods when combined with region covari-ance often require complex computation. We present an approach to transform a(More)
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