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finite-sum optimization

Description: Finite-sum optimization studies methods for minimizing objective functions formed as sums of finitely many component functions, often in machine learning and data analysis.
OpenAlex ID: keywords/finite-sum-optimization
Minimizing finite sums with the stochastic average gradient
2016 · Mark Schmidt, Nicolas Le Roux, et al. · Mathematical Programming · 922
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Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks
2020 · Zhaoxian Wu, Qing Ling, et al. · IEEE Transactions on Signal Processing · 225
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Stochastic Frank-Wolfe methods for nonconvex optimization
2016 · Sashank J. Reddi, Suvrit Sra, et al. · Allerton Conference on Communication, Control, and Computing · 149
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Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds
2016 · Zhang, Hongyi, Reddi, Sashank J., et al. · arXiv (Cornell University) · 131
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A General Framework for Decentralized Optimization With First-Order Methods
2020 · Ran Xin, Shi Pu, et al. · Proceedings of the IEEE · 109
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Why random reshuffling beats stochastic gradient descent
2019 · M. Gürbüzbalaban, A. Ozdaglar, et al. · Mathematical Programming · 102
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Proximal stochastic methods for nonsmooth nonconvex finite-sum optimization
2016 · Sashank J. Reddi, Suvrit Sra, et al. · neural information processing systems · 101
Variance-Reduced Decentralized Stochastic Optimization With Accelerated Convergence
2020 · Ran Xin, Usman A. Khan, et al. · IEEE Transactions on Signal Processing · 98
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An investigation of Newton-Sketch and subsampled Newton methods
2020 · Albert S. Berahas, Raghu Bollapragada, et al. · Optimization methods & software · 86
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Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
2017 · Xu, Pan, Chen, Jinghui, et al. · arXiv (Cornell University) · 86
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A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
2018 · Li, Zhize, Li, Jian · arXiv (Cornell University) · 70
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Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity
2018 · Du, Simon S., Hu, Wei · arXiv (Cornell University) · 69
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Stochastic Nested Variance Reduction for Nonconvex Optimization
2018 · Zhou, Dongruo, Xu, Pan, et al. · arXiv (Cornell University) · 67
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Better Theory for SGD in the Nonconvex World
2020 · Khaled, Ahmed, Richtárik, Peter · arXiv (Cornell University) · 60
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Stochastic distributed learning with gradient quantization and double-variance reduction
2022 · Samuel Horváth, Dmitry Kovalev, et al. · Optimization methods & software · 51
Finite-sum Composition Optimization via Variance Reduced Gradient Descent
2016 · Lian, Xiangru, Wang, Mengdi, et al. · arXiv (Cornell University) · 50
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Finite-sum smooth optimization with SARAH
2022 · Lam M. Nguyen, Marten van Dijk, et al. · Computational Optimization and Applications · 43
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Reduced variance deep reinforcement learning with temporal logic specifications
2019 · Qitong Gao, Davood Hajinezhad, et al. · ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS) · 43
Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds
2019 · Pan Zhou, Xiao-Tong Yuan, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 35
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Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization.
2018 · Dongruo Zhou, Pan Xu, et al. · neural information processing systems · 35
Convergence Rate of Incremental Gradient and Incremental Newton Methods
2019 · M. Gürbüzbalaban, A. Ozdaglar, et al. · SIAM Journal on Optimization · 33
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A hybrid stochastic optimization framework for composite nonconvex optimization
2021 · Quoc Tran-Dinh, Nhan H. Pham, et al. · Mathematical Programming · 32
Random Reshuffling: Simple Analysis with Vast Improvements
2020 · Mishchenko, Konstantin, Khaled, Ahmed, et al. · arXiv (Cornell University) · 32
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A Stochastic Composite Gradient Method with Incremental Variance Reduction
2019 · Zhang, Junyu, Xiao, Lin · arXiv (Cornell University) · 32
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MultiLevel Composite Stochastic Optimization via Nested Variance Reduction
2021 · Junyu Zhang, Lin Xiao · SIAM Journal on Optimization · 31
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Works count: 288
Citation count: 3,859
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