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DiSCO: Distributed Optimization for Self-Concordant Empirical Loss

Published on Dec 05, 20151886 Views

We propose a new distributed algorithm for empirical risk minimization in machine learning. The algorithm is based on an inexact damped Newton method, where the inexact Newton steps are computed by a

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