Zheng Xu

Cited by

	All	Since 2016
Citations	2182	2114
h-index	20	19
i10-index	21	21

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2013201420152016201720182019202020219 6 27 48 107 250 524 1138 37

Co-authors

Tom GoldsteinPerotto Associate Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Christoph StuderAssociate Professor at the Dept. of Information Technology and Electrical Engineering, ETH ZurichVerified email at ethz.ch
Gavin TaylorUS Naval AcademyVerified email at usna.edu
Hao LiAmazon Web ServicesVerified email at amazon.com
Mario A. T. FigueiredoInstituto de Telecomunicações; Instituto Superior Técnico, Universidade de Lisboa, PortugalVerified email at ist.utl.pt
Ali ShafahiGraduate Research Assistant, University of MarylandVerified email at umd.edu
Soham DeDeepMindVerified email at google.com
John P. DickersonAssistant Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Larry DavisProfessor of Computer Science, University of MarylandVerified email at cs.umd.edu
Mahyar NajibiUniversity of MarylandVerified email at cs.umd.edu
Amin GhiasiGraduate Research Assistant, University of MarylandVerified email at umd.edu
Dong Xu, IEEE Fellow, Chair in Comp...University of SydneyVerified email at sydney.edu.au
Wen LiData Intelligence Group, UESTCVerified email at uestc.edu.cn
Xitong YANGGraduate student of Computer Science, Univerisity of Maryland, College ParkVerified email at cs.umd.edu
Xiaoming YuanThe University of Hong KongVerified email at hku.hk
Louiqa RaschidProfessor, University of MarylandVerified email at umiacs.umd.edu
Yen-Chang HsuSamsung Research AmericaVerified email at gatech.edu
Luc Van Goolprofessor computer vision ETH Zurich & KU Leuven, Head Toyota Lab TRACE @ KUL & ETHVerified email at ethz.ch
Li NiuShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Karthik Abinav SankararamanFacebook, University of Maryland, College ParkVerified email at fb.com

Zheng Xu

Google Research

Verified email at cs.umd.edu - Homepage

Machine Learning Optimization Computer Vision Federated Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Visualizing the loss landscape of neural nets H Li, Z Xu, G Taylor, C Studer, T Goldstein Advances in Neural Information Processing Systems, 6391-6401, 2018	496	2018
Advances and Open Problems in Federated Learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... arXiv preprint arXiv:1912.04977, 2019	413	2019
Adversarial Training for Free! A Shafahi, M Najibi, A Ghiasi, Z Xu, J Dickerson, C Studer, LS Davis, ... Conference on Neural Information Processing Systems (NeurIPS), 2019	206	2019
Training neural networks without gradients: A scalable ADMM approach G Taylor, R Burmeister, Z Xu, B Singh, A Patel, T Goldstein International Conference on Machine Learning (ICML), 2722-2731, 2016	174	2016
Exploiting Low-Rank Structure from Latent Domains for Domain Generalization Z Xu, W Li, L Niu, D Xu European Conference on Computer Vision (ECCV), 628-643, 2014	121	2014
Training Quantized Nets: A Deeper Understanding H Li, S De, Z Xu, C Studer, H Samet, T Goldstein Conference on Neural Information Processing Systems (NIPS), 2017	111	2017
Towards Perceptual Image Dehazing by Physics-based Disentanglement and Adversarial Training X Yang, Z Xu, J Luo AAAI Conference on Artificial Intelligence (AAAI), 2018	73	2018
Domain Generalization and Adaptation using Low Rank Exemplar SVMs W Li, Z Xu, D Xu, D Dai, LV Gool IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017	68	2017
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks Z Xu, YC Hsu, J Huang arXiv preprint arXiv:1709.00513, 2017	67*	2017
Adaptive ADMM with Spectral Penalty Parameter Selection Z Xu, MAT Figueiredo, T Goldstein International Conference on Artificial Intelligence and Statistics (AISTATS), 2017	62	2017
Mining Visualness Z Xu, XJ Wang, CW Chen IEEE International Conference on Multimedia and Expo (ICME), 2013	55*	2013
Stabilizing Adversarial Nets With Prediction Methods A Yadav, S Shah, Z Xu, D Jacobs, T Goldstein International Conference on Learning Representations (ICLR), 2018	51	2018
Universal Adversarial Training A Shafahi, M Najibi, Z Xu, J Dickerson, LS Davis, T Goldstein AAAI Conference on Artificial Intelligence (AAAI), 2020	44	2020
Adaptive Consensus ADMM for Distributed Optimization Z Xu, G Taylor, H Li, M Figueiredo, X Yuan, T Goldstein International Conference on Machine Learning (ICML), 2017	34	2017
Towards indexing representative images on the web XJ Wang, Z Xu, L Zhang, C Liu, Y Rui Proceedings of the 20th ACM international conference on Multimedia, 1229-1238, 2012	33	2012
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent KA Sankararaman, S De, Z Xu, WR Huang, T Goldstein International Conference on Machine Learning (ICML), 2019	28*	2019
An Empirical Study of ADMM for Nonconvex Problems Z Xu, S De, MAT Figueiredo, C Studer, T Goldstein NIPS workshop on nonconvex optimization, 2016	28*	2016
Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation Z Xu, M Figueiredo, X Yuan, C Studer, T Goldstein IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017	26	2017
Strong Baseline for Single Image Dehazing with Deep Features and Instance Normalization Z Xu, X Yang, X Li, X Sun British Machine Vision Conference (BMVC), 2018	22*	2018
Learning to Cluster for Proposal-Free Instance Segmentation YC Hsu, Z Xu, Z Kira, J Huang 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018	21	2018

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