Robust Subspace Clustering with Compressed Data
IEEE Transactions on Image Processing, pp. 5161-5170, 2019.
Dimension reduction is widely regarded as an effective way for decreasing the computation, storage, and communication loads of data-driven intelligent systems, leading to a growing demand for statistical methods that allow analysis (e.g., clustering) of compressed data. We therefore study in this paper a novel problem called compressive r...More
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