An Xu

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All published works

Action	Title	Year	Authors
+ PDF Chat	Coordinating Momenta for Cross-Silo Federated Learning	2022	An Xu Heng Huang
+ PDF Chat	Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation	2022	An Xu Wenqi Li Pengfei Guo Dong Yang Holger R. Roth Ali Hatamizadeh Can Zhao Daguang Xu Heng Huang Ziyue Xu
+ PDF Chat	Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation	2022	Pengfei Guo Dong Yang Ali Hatamizadeh An Xu Ziyue Xu Wenqi Li Can Zhao Daguang Xu Stephanie A. Harmon Evrim Türkbey
+ PDF Chat	Step-Ahead Error Feedback for Distributed Training with Compressed Gradient	2021	An Xu Zhouyuan Huo Heng Huang
+	Double Momentum SGD for Federated Learning.	2021	An Xu Heng Huang
+	Training Faster with Compressed Gradient	2020	An Xu Zhouyuan Huo Heng Huang
+ PDF Chat	On the Acceleration of Deep Learning Model Parallelism With Staleness	2020	An Xu Zhouyuan Huo Heng Huang
+	Exploit Where Optimizer Explores via Residuals	2020	An Xu Zhouyuan Huo Heng Huang
+	Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training	2020	An Xu Zhouyuan Huo Heng Huang
+	Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning	2020	Bin Gu An Xu Zhouyuan Huo Cheng Deng Heng Huang
+	Step-Ahead Error Feedback for Distributed Training with Compressed Gradient	2020	An Xu Zhouyuan Huo Heng Huang
+	Diversely Stale Parameters for Efficient Training of CNNs	2019	An Xu Zhouyuan Huo Heng Huang
+	Relationships between Perron–Frobenius eigenvalue and measurements of loops in networks	2018	Lei Chen Yingxin Kou Zhanwu Li An Xu Yizhe Chang
+ PDF Chat	Elastic local breakout strategy and implementation for delay-sensitive packets with local significance	2017	Yongkang Li Zhiyuan Jiang An Xu Sheng Zhou Zhisheng Niu
+	Elastic Local Breakout Strategy and Implementation for Delay-Sensitive Packets with Local Significance	2017	Yongkang Li Zhiyuan Jiang An Xu Sheng Zhou Zhisheng Niu
+	Stability Analysis of Fractional Delay Differential Equations by Lagrange Polynomial	2012	Xiang Mei Zhang An Xu Xian Zhou Guo

Common Coauthors

Coauthor	Papers Together
Heng Huang	11
Zhouyuan Huo	8
Ziyue Xu	2
Holger R. Roth	2
Daguang Xu	2
Wenqi Li	2
Yongkang Li	2
Sheng Zhou	2
Zhisheng Niu	2
Ali Hatamizadeh	2
Zhiyuan Jiang	2
Francesca Patella	1
Yingxin Kou	1
Can Zhao	1
Can Zhao	1
Elvira Stellato	1
Xian Zhou Guo	1
Lei Chen	1
Dong Yang	1
Bin Gu	1
Pengfei Guo	1
Zhanwu Li	1
Gianpaolo Carrafiello	1
Vishal M. Patel	1
Cheng Deng	1
Barış Türkbey	1
Bradford J. Wood	1
Dong Yang	1
Yizhe Chang	1
Xiang Mei Zhang	1
Stephanie A. Harmon	1
Evrim Türkbey	1
Pengfei Guo	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	8
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	6
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	5
+	Local SGD Converges Fast and Communicates Little	2018	Sebastian U. Stich	5
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	5
+ PDF Chat	Sparse Communication for Distributed Gradient Descent	2017	Alham Fikri Aji Kenneth Heafield	4
+	Error Feedback Fixes SignSGD and other Gradient Compression Schemes	2019	Sai Praneeth Karimireddy Quentin Rebjock Sebastian U. Stich Martin Jaggi	4
+	Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training	2018	Yujun Lin Song Han Huizi Mao Yu Wang William J. Dally	4
+	The Convergence of Sparsified Gradient Methods	2018	Dan Alistarh Torsten Hoefler Mikael Johansson Nikola Konstantinov Sarit Khirirat Cédric Renggli	4
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	4
+	Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification	2019	Harry Chia-Hung Hsu Hang Qi Matthew A. Brown	3
+	Variance Reduced Local SGD with Lower Communication Complexity	2019	Xianfeng Liang Shuheng Shen Jingchang Liu Zhen Pan Enhong Chen Yifei Cheng	3
+	TernGrad: ternary gradients to reduce communication in distributed deep learning	2017	Wei Wen Cong Xu Feng Yan Chunpeng Wu Yandan Wang Yiran Chen Hai Li	3
+	Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning	2021	Pengfei Guo Puyang Wang Jinyuan Zhou Shanshan Jiang Vishal M. Patel	3
+	Unified Convergence Analysis of Stochastic Momentum Methods for Convex and Non-convex Optimization	2016	Tianbao Yang Qihang Lin Zhe Li	3
+	Training Neural Networks Using Features Replay.	2018	Zhouyuan Huo Bin Gu Heng Huang	3
+	Federated Learning: Strategies for Improving Communication Efficiency	2016	Jakub Konečný H. Brendan McMahan Felix X. Yu Peter Richtárik Ananda Theertha Suresh Dave Bacon	3
+	Federated Learning: Strategies for Improving Communication Efficiency	2016	Jakub Konečný H. Brendan McMahan Felix X. Yu Peter Richtárik Ananda Theertha Suresh Dave Bacon	3
+	signSGD: Compressed Optimisation for Non-Convex Problems	2018	Jeremy Bernstein Yu-Xiang Wang Kamyar Azizzadenesheli Animashree Anandkumar	3
+	Asynchronous Decentralized Parallel Stochastic Gradient Descent	2017	Xiangru Lian Wei Zhang Ce Zhang Ji Liu	3
+	Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training	2020	An Xu Zhouyuan Huo Heng Huang	3
+	QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding	2016	Dan Alistarh Demjan Grubic Jerry Li Ryota Tomioka Milan Vojnović	3
+	D$^2$: Decentralized Training over Decentralized Data	2018	Hanlin Tang Xiangru Lian Ming Yan Ce Zhang Ji Liu	3
+	Sparsified SGD with Memory	2018	Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi	3
+ PDF Chat	Going deeper with convolutions	2015	Christian Szegedy Wei Liu Yangqing Jia Pierre Sermanet Scott Reed Dragomir Anguelov Dumitru Erhan Vincent Vanhoucke Andrew Rabinovich	3
+	Communication Compression for Decentralized Training	2018	Hanlin Tang Shaoduo Gan Ce Zhang Tong Zhang Liu Ji	3
+	Improving Federated Learning Personalization via Model Agnostic Meta Learning	2019	Yihan Jiang Jakub Konečný Keith Rush Sreeram Kannan	2
+	Momentum-Based Variance Reduction in Non-Convex SGD	2019	Ashok Cutkosky Francesco Orabona	2
+	Ouroboros: On Accelerating Training of Transformer-Based Language Models	2019	Qian Yang Zhouyuan Huo Wenlin Wang Heng Huang Lawrence Carin	2
+ PDF Chat	Five disruptive technology directions for 5G	2014	Federico Boccardi Robert W. Heath Angel Lozano Thomas L. Marzetta Petar Popovski	2
+	Direct Feedback Alignment Provides Learning in Deep Neural Networks	2016	Arild Nøkland	2
+	$\texttt{DeepSqueeze}$: Decentralization Meets Error-Compensated Compression	2019	Hanlin Tang Xiangru Lian Shuang Qiu Lei Yuan Ce Zhang Tong Zhang Ji Liu	2
+ PDF Chat	Aggregated Residual Transformations for Deep Neural Networks	2017	Saining Xie Ross Girshick Piotr Dollár Zhuowen Tu Kaiming He	2
+ PDF Chat	Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification	2015	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	2
+	Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients	2019	Jun Sun Tianyi Chen Georgios B. Giannakis Zaiyue Yang	2
+	GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism	2018	Yanping Huang Youlong Cheng Ankur Bapna Orhan Fırat Mia Xu Chen Dehao Chen HyoukJoong Lee Jiquan Ngiam Quoc V. Le Yonghui Wu	2
+ PDF Chat	Densely Connected Convolutional Networks	2017	Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger	2
+ PDF Chat	Squeeze-and-Excitation Networks	2019	Jie Hu Li Shen Samuel Albanie Gang Sun Enhua Wu	2
+	LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning	2018	Tianyi Chen Georgios B. Giannakis Tao Sun Wotao Yin	2
+	Rethinking the Value of Network Pruning	2018	Zhuang Liu Mingjie Sun Tinghui Zhou Gao Huang Trevor Darrell	2
+	Training Deep Nets with Sublinear Memory Cost	2016	Tianqi Chen Bing Xu Chiyuan Zhang Carlos Guestrin	2
+	SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives	2014	Aaron Defazio Francis Bach Simon Lacoste-Julien	2
+	One weird trick for parallelizing convolutional neural networks	2014	Alex Krizhevsky	2
+	Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback	2019	Shuai Zheng Ziyue Huang James T. Kwok	2
+ PDF Chat	Decoupled Greedy Learning of CNNs	2020	Eugene Belilovsky Michael Eickenberg Edouard Oyallon	2
+	Fair Resource Allocation in Federated Learning	2019	Li Tian Maziar Sanjabi Ahmad Beirami Virginia Smith	2
+	MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems	2015	Tianqi Chen Mu Li Yutian Li Min Lin Naiyan Wang Minjie Wang Tianjun Xiao Bing Xu Chiyuan Zhang Zheng Zhang	2
+	Agnostic Federated Learning	2019	Mehryar Mohri Gary Sivek Ananda Theertha Suresh	2
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	2
+ PDF Chat	Rethinking the Inception Architecture for Computer Vision	2016	Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jon Shlens Zbigniew Wojna	2