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math.NA2013★ 53 cited
Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning
Zhouchen Lin, Risheng Liu, Huan Li
Many problems in machine learning and other fields can be (re)for-mulated as linearly constrained separable convex programs. In most of the cases, there are multiple blocks of vari…
math.NA2011★ 28 cited
Solving Principal Component Pursuit in Linear Time via Filtering
Risheng Liu, Zhouchen Lin, Siming Wei +1
In the past decades, exactly recovering the intrinsic data structure from corrupted observations, which is known as robust principal component analysis (RPCA), has attracted tremen…
math.NA2010★ 130 cited
Low-Rank Structure Learning via Log-Sum Heuristic Recovery
Yue Deng, Qionghai Dai, Risheng Liu +2
Recovering intrinsic data structure from corrupted observations plays an important role in various tasks in the communities of machine learning and signal processing. In this paper…