FENG Hui, TANG Xianding, YANG Tao, et al., “Split Method of Multipliers and Its Application to Parallel and Distributed Logistic Regression,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 305-310, 2014,
Citation: FENG Hui, TANG Xianding, YANG Tao, et al., “Split Method of Multipliers and Its Application to Parallel and Distributed Logistic Regression,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 305-310, 2014,

Split Method of Multipliers and Its Application to Parallel and Distributed Logistic Regression

Funds:  This work is supported by the National Science and Technology Major Project of China (No.2012ZX03001007-003).
  • Received Date: 2012-06-01
  • Rev Recd Date: 2013-05-01
  • Publish Date: 2014-04-05
  • We consider the scenario where two variables need to be optimized simultaneously. The minimization over one variable has an analytical solution, while it is intractable for the other. Under the Lagrangian dual framework, we propose two iterative optimization algorithms, which make partial minimization and gradient descent alternatingly over two variables. The first algorithm asserts that the iteration result converges to a KKT point under proper stepsize rules, which only needs the augmented Lagrangian function to be convex over partial variable. The second algorithm provides the local attraction property around the KKT point. Our algorithms provide a general solution to parallel and distributed optimization with summable objective functions. Simulation results on parallel and distributed logistic regression classification are present, which show faster convergence rate with less computational complexity compared with other methods.
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