A Randomized Nonlinear Rescaling Method in Large-Scale Constrained Convex Optimization

24 Mar 2020 Wei Bo Haskell William B. Zhao Sixiang

We propose a new randomized algorithm for solving convex optimization problems that have a large number of constraints (with high probability). Existing methods like interior-point or Newton-type algorithms are hard to apply to such problems because they have expensive computation and storage requirements for Hessians and matrix inversions... (read more)

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