finite-sum minimization

Reusing Samples in Variance Reduction ALT 2026 Efficient Continual Finite-Sum Minimization ICLR 2024 Tighter Lower Bounds for Shuffling SGD: Random Permutations and Beyond ICML 2023 Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization NeurIPS 2022 Asynchronous Distributed Optimization with Stochastic Delays AISTATS 2022 Nesterov Accelerated Shuffling Gradient Method for Convex Optimization ICML 2022 Proximal and Federated Random Reshuffling ICML 2022 An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders NeurIPS 2021 Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator ICML 2019 Breaking the Span Assumption Yields Fast Finite-Sum Minimization NeurIPS 2018 New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity NeurIPS 2018 Towards Memory-Friendly Deterministic Incremental Gradient Method AISTATS 2018 SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient ICML 2017 Accelerated Stochastic Gradient Descent for Minimizing Finite Sums AISTATS 2016