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Block Splitting for Large-Scale Distributed Learning
Block Splitting Large-Scale Distributed Learning
2015/7/9
Machine learning and statistics with very large datasets is now a topic of widespread interest, both in academia and industry. Many such tasks can be posed as convex optimization problems, so algorith...
Block Splitting for Distributed Optimization
Distributed optimization · Alternating direction method of multipliers Operator splitting Proximal operators Cone programming Machine learning
2015/7/9
This paper describes a general purpose method for solving convex optimization problems in a distributed computing environment. In particular, if the problem data includes a large linear operator or ma...
Stable and efficient updates to the basis matrix factors are vital to the simplex
method. The "best" updating method depends on the machine in use and how the update is implemented. For example, the ...