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On the Optimality of Averaging in Distributed Statistical Learning

10 July 2014

Jonathan D. Rosenblatt

B. Nadler

FedML

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Papers citing "On the Optimality of Averaging in Distributed Statistical Learning"

46 / 46 papers shown

Title
High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates Fred Lu Ryan R. Curtin Edward Raff Francis Ferraro James Holt 63 1 0 08 Jul 2024
Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification Fred Lu Ryan R. Curtin Edward Raff Francis Ferraro James Holt 123 0 0 03 Jun 2024
A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques Xuetong Li Yuan Gao Hong Chang Danyang Huang Yingying Ma ... Ke Xu Jing Zhou Xuening Zhu Yingqiu Zhu Hansheng Wang 68 9 0 17 Mar 2024
Copula Approximate Bayesian Computation Using Distribution Random Forests G. Karabatsos 68 1 0 28 Feb 2024
Byzantine-robust distributed one-step estimation Chuhan Wang Xuehu Zhu Lixing Zhu OOD 18 0 0 15 Jul 2023
A review of distributed statistical inference Yuan Gao Weidong Liu Hansheng Wang Xiaozhou Wang Yibo Yan Riquan Zhang 74 43 0 13 Apr 2023
Distributed Sparse Linear Regression under Communication Constraints R. Fonseca B. Nadler FedML 74 2 0 09 Jan 2023
Recovery Guarantees for Distributed-OMP Chen Amiraz Robert Krauthgamer B. Nadler 79 0 0 15 Sep 2022
ReBoot: Distributed statistical learning via refitting bootstrap samples Yumeng Wang Ziwei Zhu Xuming He FedML BDL 31 1 0 19 Jul 2022
Communication-efficient Distributed Newton-like Optimization with Gradients and M-estimators Ziyan Yin 77 0 0 13 Jul 2022
Distributed Sparse Regression via Penalization Yao Ji G. Scutari Ying Sun Harsha Honnappa 65 6 0 12 Nov 2021
Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective Margalit Glasgow Honglin Yuan Tengyu Ma FedML 79 45 0 05 Nov 2021
Data splitting improves statistical performance in overparametrized regimes Nicole Mücke Enrico Reiss Jonas Rungenhagen Markus Klein 55 8 0 21 Oct 2021
Communication-efficient SGD: From Local SGD to One-Shot Averaging Artin Spiridonoff Alexander Olshevsky I. Paschalidis FedML 102 20 0 09 Jun 2021
Uncertainty quantification for distributed regression V. Avanesov UQCV 20 0 0 24 May 2021
Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inference Jiyuan Tu Weidong Liu Xiaojun Mao Xi Chen 56 20 0 04 Mar 2021
Distributed Sparse Normal Means Estimation with Sublinear Communication Chen Amiraz Robert Krauthgamer B. Nadler FedML 58 2 0 05 Feb 2021
Federated Composite Optimization Honglin Yuan Manzil Zaheer Sashank J. Reddi FedML 87 61 0 17 Nov 2020
Communication-efficient distributed eigenspace estimation Vasileios Charisopoulos Austin R. Benson Anil Damle 47 10 0 05 Sep 2020
Federated Accelerated Stochastic Gradient Descent Honglin Yuan Tengyu Ma FedML 102 180 0 16 Jun 2020
Local SGD With a Communication Overhead Depending Only on the Number of Workers Artin Spiridonoff Alexander Olshevsky I. Paschalidis FedML 61 19 0 03 Jun 2020
Distributed function estimation: adaptation using minimal communication Botond Szabó Harry Van Zanten 66 13 0 28 Mar 2020
Scalable Approximate Inference and Some Applications Jun Han BDL 59 1 0 07 Mar 2020
Is Local SGD Better than Minibatch SGD? Blake E. Woodworth Kumar Kshitij Patel Sebastian U. Stich Zhen Dai Brian Bullins H. B. McMahan Ohad Shamir Nathan Srebro FedML 91 254 0 18 Feb 2020
$DC^2$ : A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering Ke Alexander Wang Xinran Bian Pan Liu Donghui Yan 125 4 0 16 Nov 2019
Learning over inherently distributed data Donghui Yan Ying Xu FedML 125 2 0 30 Jul 2019
Communication-Efficient Accurate Statistical Estimation Jianqing Fan Yongyi Guo Kaizheng Wang 61 114 0 12 Jun 2019
Communication trade-offs for synchronized distributed SGD with large step size Kumar Kshitij Patel Aymeric Dieuleveut FedML 66 27 0 25 Apr 2019
A Global Bias-Correction DC Method for Biased Estimation under Memory Constraint Lu Lin Feng Li 40 2 0 16 Apr 2019
WONDER: Weighted one-shot distributed ridge regression in high dimensions Yan Sun Yueqi Sheng OffRL 92 51 0 22 Mar 2019
Effective Parallelisation for Machine Learning Michael Kamp Mario Boley Olana Missura Thomas Gärtner 47 12 0 08 Oct 2018
Distributed linear regression by averaging Yan Sun Yueqi Sheng FedML 94 66 0 30 Sep 2018
Adaptive distributed methods under communication constraints Botond Szabó Harry Van Zanten 80 24 0 03 Apr 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 160 1,529 0 05 Mar 2018
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network Zheng-Chu Guo Lei Shi Qiang Wu 41 43 0 07 Aug 2017
Accelerating Stochastic Gradient Descent For Least Squares Regression Prateek Jain Sham Kakade Rahul Kidambi Praneeth Netrapalli Aaron Sidford 80 84 0 26 Apr 2017
Distributed Statistical Estimation and Rates of Convergence in Normal Approximation Stanislav Minsker Nate Strawn 86 67 0 09 Apr 2017
Communication-efficient Distributed Estimation and Inference for Transelliptical Graphical Models Pan Xu Lu Tian Quanquan Gu FedML 46 7 0 29 Dec 2016
Greedy Step Averaging: A parameter-free stochastic optimization method Xiatian Zhang Fan Yao Yongjun Tian 31 0 0 11 Nov 2016
Communication-efficient Distributed Sparse Linear Discriminant Analysis Lu Tian Quanquan Gu 69 23 0 15 Oct 2016
Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification Prateek Jain Sham Kakade Rahul Kidambi Praneeth Netrapalli Aaron Sidford MoMe 101 36 0 12 Oct 2016
Bootstrap Model Aggregation for Distributed Statistical Learning J. Han Qiang Liu FedML 80 10 0 04 Jul 2016
Efficient Distributed Learning with Sparsity Jialei Wang Mladen Kolar Nathan Srebro Tong Zhang FedML 90 152 0 25 May 2016
A Distributed One-Step Estimator Cheng Huang X. Huo FedML 134 84 0 04 Nov 2015
Communication-efficient sparse regression: a one-shot approach Jason D. Lee Yuekai Sun Qiang Liu Jonathan E. Taylor 120 66 0 14 Mar 2015
A simple scheme for the parallelization of particle filters and its application to the tracking of complex stochastic systems Dan Crisan Joaquín Míguez Gonzalo Rios 112 7 0 30 Jul 2014