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Distributed Optimization with Arbitrary Local Solvers
Chenxin Ma, Jakub Konečný, Martin Jaggi +4
With the growth of data and necessity for distributed optimization methods, solvers that work well on a single machine must be re-designed to leverage distributed computation. Rece…
L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework
Virginia Smith, Simone Forte, Michael I. Jordan +1
Despite the importance of sparsity in many large-scale applications, there are few methods for distributed optimization of sparsity-inducing objectives. In this paper, we present a…
Adding vs. Averaging in Distributed Primal-Dual Optimization
Chenxin Ma, Virginia Smith, Martin Jaggi +3
Distributed optimization methods for large-scale machine learning suffer from a communication bottleneck. It is difficult to reduce this bottleneck while still efficiently and accu…