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Generalizations of the Alternating Direction Method of Multipliers for Large-Scale and Distributed Optimization
Due to the dramatically increasing demand for dealing with "Big Data", efficient and scalable computational methods are highly desirable to cope with the size of the data. The alternating direction method of multipliers ...
Recovering Data with Group Sparsity by Alternating Direction Methods
Group sparsity reveals underlying sparsity patterns and contains rich structural information in data. Hence, exploiting group sparsity will facilitate more efficient techniques for recovering large and complicated data in ...