Fetching the paper…
Reading the bibliography…
Stochastic gradient descent without replacement sampling is widely used in practice for model training.
Curiously fast convergence of some stochastic gradient descent algorithms
Léon Bottou · 2009
Earlier work this paper cites.
On gospers formula for the gamma function
Cristinel Mortici · 2011
Earlier work this paper cites.
Benjamin Recht and Christopher Ré · 2012
Earlier work this paper cites.
Parallel stochastic gradient algorithms for large-scale matrix completion
Benjamin Recht and Christopher Ré · 2013
Earlier work this paper cites.
Introductory lectures on convex optimization: A basic course , volume 87
Yurii Nesterov · 2013
Earlier work this paper cites.
Convex optimization: Algorithms and complexity
Sébastien Bubeck et al · 2015
Earlier work this paper cites.
Why random reshuffling beats stochastic gradient descent
Mert Gürbüzbalaban, Asu Ozdaglar, and PA Parrilo · 2015
Cited alongside, same era.
Without-replacement sampling for stochastic gradient methods
Ohad Shamir · 2016
Cited alongside, same era.
Analyzing random permutations for cyclic coordinate descent
Stephen J Wright and Ching-pei Lee · 2017
Cited alongside, same era.
Random shuffling beats sgd after finite epochs
Jeffery Z HaoChen and Suvrit Sra · 2018
Cited alongside, same era.
Stochastic learning under random reshuffling with constant step-sizes
Bicheng Ying, Kun Yuan, Stefan Vlaski, and Ali H Sayed · 2018
Cited alongside, same era.
Sgd without replacement: Sharper rates for general smooth convex functions
Dheeraj Nagaraj, Prateek Jain, and Praneeth Netrapalli · 2019
Later among the works it cites.
Random permutations fix a worst case for cyclic coordinate descent
Ching-Pei Lee and Stephen J Wright · 2019
Later among the works it cites.
Worst-case complexity of cyclic coordinate descent: 𝒪 ( n 2 ) \mathcal{O}(n^{2}) gap with randomized version
Ruoyu Sun and Yinyu Ye · 2019
Later among the works it cites.
On the efficiency of random permutation for admm and coordinate descent
Ruoyu Sun, Zhi-Quan Luo, and Yinyu Ye · 2019
Later among the works it cites.
Convergence analysis of distributed stochastic gradient descent with shuffling
Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, and Tie-Yan Liu · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Itay Safran and Ohad Shamir · 2019
Cited alongside, same era.
Randomness and permutations in coordinate descent methods
Mert Gurbuzbalaban, Asuman Ozdaglar, Nuri Denizcan Vanli, and Stephen J Wright
Cited in the paper.
Convergence rate of incremental gradient and incremental newton methods
M Gurbuzbalaban, A Ozdaglar, and PA Parrilo
Cited in the paper.