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Found 5 papers, 2 papers with code
A Stochastic Proximal Method for Nonsmooth Regularized Finite Sum Optimization
We consider the problem of training a deep neural network with nonsmooth regularization to retrieve a sparse and efficient sub-structure.
Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learning
In this paper, we consider both first- and second-order techniques to address continuous optimization problems arising in machine learning.
A Julia implementation of Algorithm NCL for constrained optimization
We give numerical results from a Julia implementation of Algorithm NCL on tax policy models that do not satisfy the LICQ, and on nonlinear least-squares problems and general problems from the CUTEst test set.
Optimization and Control Numerical Analysis Numerical Analysis
Stochastic Damped L-BFGS with Controlled Norm of the Hessian Approximation
We propose a new stochastic variance-reduced damped L-BFGS algorithm, where we leverage estimates of bounds on the largest and smallest eigenvalues of the Hessian approximation to balance its quality and conditioning.
Constraint-Preconditioned Krylov Solvers for Regularized Saddle-Point Systems
We consider the iterative solution of regularized saddle-point systems.
Numerical Analysis Numerical Analysis 65F08, 65F10, 65F50, 90C20
