Distributed Optimization and Statistical Learning via the ...

Foundations and TrendsR inMachine LearningVol. 3, No. 1 (2010) 1 122c 2011 S. Boyd, N. Parikh, E. Chu, B. Peleatoand J. EcksteinDOI: Optimization and StatisticalLearning via the Alternating DirectionMethod of MultipliersStephen Boyd1, Neal Parikh2, Eric Chu3 Borja Peleato4and Jonathan Eckstein51 Electrical Engineering Department, Stanford University, Stanford, CA94305, USA, Science Department, Stanford University, Stanford, CA 94305,USA, Engineering Department, Stanford University, Stanford, CA94305, USA, Engineering Department, Stanford University, Stanford, CA94305, USA, Science and Information Systems Department andRUTCOR, Rutgers University, Piscataway, NJ 08854.

The method was developed in the 1970s, with roots in the 1950s, and is equivalent or closely related to many other algorithms, such ... share some key characteristics. First, the datasets are often extremely large, consisting of hundreds of millions or billions of training examples;

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