Machine Learning · Computer Science
A Parallel SGD method with Strong Convergence
Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan, Leon Bottou
2013-11-05
Optimization and Control · Mathematics
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent
Eduard Gorbunov, Filip Hanzely, Peter Richtárik
2019-05-28
Machine Learning · Computer Science
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos +1
2016-01-26
Optimization and Control · Mathematics
Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness
Thinh T. Doan, Lam M. Nguyen, Nhan H. Pham, Justin Romberg
2020-04-02
Machine Learning · Computer Science
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions
Yunwen Lei, Ting Hu, Guiying Li, Ke Tang
2019-12-16
Machine Learning · Computer Science
Demystifying the Myths and Legends of Nonconvex Convergence of SGD
Aritra Dutta, El Houcine Bergou, Soumia Boucherouite, Nicklas Werge +2
2023-10-20
Optimization and Control · Mathematics
Error Lower Bounds of Constant Step-size Stochastic Gradient Descent
Zhiyan Ding, Yiding Chen, Qin Li, Xiaojin Zhu
2019-10-21