adaptive step size

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization NeurIPS 2022 Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution NeurIPS 2022 Making SGD Parameter-Free COLT 2022 On the Last Iterate Convergence of Momentum Methods ALT 2022 Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs IJCAI 2022 Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent ICML 2022 Calibrated Adaptive Probabilistic ODE Solvers AISTATS 2021 "Hey, that’s not an ODE": Faster ODE Adjoints via Seminorms ICML 2021 Neurally Augmented ALISTA ICLR 2021 AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients NeurIPS 2020 Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization ACML 2020 Adaptive Proximal Average Based Variance Reducing Stochastic Methods for Optimization with Composite Regularization AAAI 2019 Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search ICML 2019 On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes AISTATS 2019 Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions ICLR 2019 Adaptive Three Operator Splitting ICML 2018 Follow the Moving Leader in Deep Learning ICML 2017 Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values ICML 2017 Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation AISTATS 2016 Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing NeurIPS 2015 Adaptive Step-size Policy Gradients with Average Reward Metric ACML 2010