Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method

22 May 2017 Mark Eisen Aryan Mokhtari Alejandro Ribeiro

We consider large scale empirical risk minimization (ERM) problems, where both the problem dimension and variable size is large. In these cases, most second order methods are infeasible due to the high cost in both computing the Hessian over all samples and computing its inverse in high dimensions... (read more)

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