The algorithm is variable-metric in the sense that, in each iteration, the step is computed through the product of a symmetric positive definite scaling matrix ...
Jun 21, 2016 · A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization. In Proceedings of the 33rd International Conference on Machine ...
The algorithm is variable-metric in the sense that, in each iteration, the step is computed through the product of a symmetric positive definite scaling matrix ...
SCBFGS (Self-Correcting BFGS Algorithm for Stochastic Optimization) is a prototype code for solving stochastic optimization problems.
An algorithm framework is proposed for minimizing nonsmooth functions. The framework is variable metric in that, in each iteration, a step is computed using a ...
Jun 4, 2016 · A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization. In Proceedings of the 33rd International Conference on Machine Learning ...
A generic algorithmic framework for minimizing nonsmooth and potentially nonconvex objective functions that exploits the self-correcting properties of ...
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This paper presents a methodology for using varying sample sizes in sequential quadratic programming (SQP) methods for solving equality constrained ...
Abstract:An algorithm framework is proposed for minimizing nonsmooth functions. The framework is variable-metric in that, in each iteration, ...
Missing: Stochastic | Show results with:Stochastic
Abstract An algorithm framework is proposed for minimizing nonsmooth functions. The framework is variable metric in that, in each iteration, a step is ...