quasi-newton method

Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization NeurIPS 2021 Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods CVPR 2021 Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach NeurIPS 2021 Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant Updates AISTATS 2021 Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence NeurIPS 2021 Quasi-Monte Carlo Quasi-Newton in Variational Bayes JMLR 2021 Smooth Bilevel Programming for Sparse Regularization NeurIPS 2021 The ensmallen library for flexible numerical optimization JMLR 2021 Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds ACML 2021 DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate AISTATS 2020 Practical Quasi-Newton Methods for Training Deep Neural Networks NeurIPS 2020 Quasi-Newton Solver for Robust Non-Rigid Registration CVPR 2020 Variance Reduction and Quasi-Newton for Particle-Based Variational Inference ICML 2020 Quasi-Newton Trust Region Policy Optimization CoRL 2019 Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization NeurIPS 2018 A Progressive Batching L-BFGS Method for Machine Learning ICML 2018 Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization ICML 2018 Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis AISTATS 2018 Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values ICML 2017 A Multi-Batch L-BFGS Method for Machine Learning NeurIPS 2016 A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization ICML 2016 Black-box Optimization with a Politician ICML 2016 Softened Approximate Policy Iteration for Markov Games ICML 2016 Stochastic Block BFGS: Squeezing More Curvature out of Data ICML 2016 Stochastic Quasi-Newton Langevin Monte Carlo ICML 2016