Yu Lu

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All published works

Action	Title	Year	Authors
+	Towards Heterogeneous Clients with Elastic Federated Learning	2021	Zichen Ma Yu Lu Zihan Lu Wenye Li Jinfeng Yi Shuguang Cui

Common Coauthors

Coauthor	Papers Together
Zichen Ma	1
Shuguang Cui	1
Jinfeng Yi	1
Zihan Lu	1
Wenye Li	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	Federated Learning: Strategies for Improving Communication Efficiency	2016	Jakub Konečný H. Brendan McMahan Felix X. Yu Peter Richtárik Ananda Theertha Suresh Dave Bacon	1
+	Continual Learning with Deep Generative Replay	2017	Hanul Shin Jung Kwon Lee Jaehong Kim Jiwon Kim	1
+	QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding	2016	Dan Alistarh Demjan Grubic Jerry Li Ryota Tomioka Milan Vojnović	1
+	Variance-based Gradient Compression for Efficient Distributed Deep Learning	2018	Yusuke Tsuzuku Hiroto Imachi Takuya Akiba	1
+	Local SGD Converges Fast and Communicates Little	2018	Sebastian U. Stich	1
+	Federated Learning with Non-IID Data	2018	Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra	1
+	Don't Use Large Mini-Batches, Use Local SGD	2018	Tao Lin Sebastian U. Stich Kumar Kshitij Patel Martin Jaggi	1
+	Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms	2018	Jianyu Wang Gauri Joshi	1
+	On the Convergence of Federated Optimization in Heterogeneous Networks.	2018	Anit Kumar Sahu Tian Li Maziar Sanjabi Manzil Zaheer Ameet Talwalkar Virginia Smith	1
+	Federated Optimization in Heterogeneous Networks	2018	Li Tian Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith	1
+	Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations	2019	Debraj Basu Deepesh Data Can Karakus Suhas Diggavi	1
+	Learning Differentially Private Recurrent Language Models	2017	H. Brendan McMahan Daniel Ramage Kunal Talwar Li Zhang	1
+	On the Convergence of FedAvg on Non-IID Data	2019	Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang	1
+	signSGD: Compressed Optimisation for Non-Convex Problems	2018	Jeremy Bernstein Yu-Xiang Wang Kamyar Azizzadenesheli Animashree Anandkumar	1
+	On the Convergence of Local Descent Methods in Federated Learning	2019	Farzin Haddadpour Mehrdad Mahdavi	1
+	Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning	2019	Xinyan Dai Yan Xiao Kaiwen Zhou Han Yang Kelvin K. W. Ng James Cheng Fan Yu	1
+	Variance Reduced Local SGD with Lower Communication Complexity	2019	Xianfeng Liang Shuheng Shen Jingchang Liu Zhen Pan Enhong Chen Yifei Cheng	1
+	Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization	2020	Zhize Li Dmitry Kovalev Xun Qian Peter Richtárik	1
+	Adaptive Personalized Federated Learning	2020	Yuyang Deng Mohammad Mahdi Kamani Mehrdad Mahdavi	1
+	SCAFFOLD: Stochastic Controlled Averaging for Federated Learning	2019	Sai Praneeth Karimireddy Satyen Kale Mehryar Mohri Sashank J. Reddi Sebastian U. Stich Ananda Theertha Suresh	1
+	Federated Heavy Hitters Discovery with Differential Privacy	2019	Wennan Zhu Peter Kairouz Brendan McMahan Haicheng Sun Wei Li	1
+	Tighter Theory for Local SGD on Identical and Heterogeneous Data	2020	Ahmed Khaled Konstantin Mishchenko Peter Richtárik	1
+	Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning	2020	Sai Praneeth Karimireddy Martin Jaggi Satyen Kale Mehryar Mohri Sashank J. Reddi Sebastian U. Stich Ananda Theertha Suresh	1
+ PDF Chat	Short-term plasticity as cause–effect hypothesis testing in distal reward learning	2014	Andrea Soltoggio	1
+ PDF Chat	Sparse Communication for Distributed Gradient Descent	2017	Alham Fikri Aji Kenneth Heafield	1
+ PDF Chat	Neurogenesis deep learning: Extending deep networks to accommodate new classes	2017	Timothy J. Draelos Nadine E. Miner Christopher C. Lamb Jonathan A. Cox Craig M. Vineyard Kristofor D. Carlson William Severa Conrad D. James James B. Aimone	1
+	On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization	2018	Fan Zhou Guojing Cong	1
+ PDF Chat	Lifelong Learning of Spatiotemporal Representations With Dual-Memory Recurrent Self-Organization	2018	German I. Parisi Jun Tani Cornelius Weber Stefan Wermter	1