Zheng Xu
Zheng Xu
Google Research
Verified email at cs.umd.edu - Homepage
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
3482018
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
1482016
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
982019
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
962014
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
922017
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
862019
Adaptive ADMM with Spectral Penalty Parameter Selection
Z Xu, MAT Figueiredo, T Goldstein
International Conference on Artificial Intelligence and Statistics (AISTATS), 2017
562017
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
522017
Mining Visualness
Z Xu, XJ Wang, CW Chen
IEEE International Conference on Multimedia and Expo (ICME), 2013
51*2013
Towards Perceptual Image Dehazing by Physics-based Disentanglement and Adversarial Training
X Yang, Z Xu, J Luo
AAAI Conference on Artificial Intelligence (AAAI), 2018
442018
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
41*2017
Stabilizing Adversarial Nets With Prediction Methods
A Yadav, S Shah, Z Xu, D Jacobs, T Goldstein
International Conference on Learning Representations (ICLR), 2018
372018
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
322012
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
292017
Universal Adversarial Training
A Shafahi, M Najibi, Z Xu, J Dickerson, LS Davis, T Goldstein
AAAI Conference on Artificial Intelligence (AAAI), 2020
252020
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
212017
An Empirical Study of ADMM for Nonconvex Problems
Z Xu, S De, MAT Figueiredo, C Studer, T Goldstein
NIPS workshop on nonconvex optimization, 2016
212016
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
17*2018
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
KA Sankararaman, S De, Z Xu, WR Huang, T Goldstein
arXiv preprint arXiv:1904.06963, 2019
14*2019
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
132018
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