RES: Regularized Stochastic BFGS Algorithm

@article{Mokhtari2014RESRS,
  title={RES: Regularized Stochastic BFGS Algorithm},
  author={Aryan Mokhtari and Alejandro Ribeiro},
  journal={IEEE Transactions on Signal Processing},
  year={2014},
  volume={62},
  pages={6089-6104}
}
RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method, is proposed to solve strongly convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second-order methods, on the other hand, is impracticable because the computation of objective function… Expand
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