Mini-Batch Stochastic ADMMs for Nonconvex Nonsmooth Optimization

arXiv: Optimization and Control, Volume abs/1802.03284, 2018.

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Abstract:

With the large rising of complex data, the nonconvex models such as nonconvex loss function and nonconvex regularizer are widely used in machine learning and pattern recognition. In this paper, we propose a class of mini-batch stochastic ADMMs (alternating direction method of multipliers) for solving large-scale nonconvex nonsmooth proble...More

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