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Wei Wen
Wei Wen
Research Scientist, AI at Meta
Подтвержден адрес электронной почты в домене fb.com - Главная страница
Название
Процитировано
Процитировано
Год
Learning Structured Sparsity in Deep Neural Networks
W Wen, C Wu, Y Wang, Y Chen, H Li
Advances In Neural Information Processing Systems, 2074-2082, 2016
30542016
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
W Wen, C Xu, F Yan, C Wu, Y Wang, Y Chen, H Li
Advances In Neural Information Processing Systems, 1508-1518, 2017
11992017
Faster cnns with direct sparse convolutions and guided pruning
J Park, S Li, W Wen, PTP Tang, H Li, Y Chen, P Dubey
International Conference on Learning Representations (ICLR), 2017
2992017
Neural predictor for neural architecture search
W Wen, H Liu, H Li, Y Chen, G Bender, PJ Kindermans
European Conference on Computer Vision (ECCV), 2020
2402020
Feature space perturbations yield more transferable adversarial examples
N Inkawhich, W Wen, HH Li, Y Chen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7066-7074, 2019
2362019
Coordinating Filters for Faster Deep Neural Networks
W Wen, C Xu, C Wu, Y Wang, Y Chen, H Li
Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017
1852017
Learning Intrinsic Sparse Structures within Long Short-term Memory
W Wen, Y He, S Rajbhandari, W Wang, F Liu, B Hu, Y Chen, H Li
International Conference on Learning Representations (ICLR), 2018
1592018
TRP: Trained Rank Pruning for Efficient Deep Neural Networks
Y Xu, Y Li, S Zhang, W Wen, B Wang, Y Qi, Y Chen, W Lin, H Xiong
International Joint Conference on Artificial Intelligence (IJCAI), 2020
147*2020
DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures
H Yang, W Wen, H Li
International Conference on Learning Representations (ICLR), 2020
1362020
PruneTrain: fast neural network training by dynamic sparse model reconfiguration
S Lym, E Choukse, S Zangeneh, W Wen, S Shanghavi, M Erez
Proceedings of the International Conference for High Performance Computing …, 2019
116*2019
Mednn: A distributed mobile system with enhanced partition and deployment for large-scale dnns
J Mao, Z Yang, W Wen, C Wu, L Song, KW Nixon, X Chen, H Li, Y Chen
2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 751-756, 2017
992017
Neu-NoC: A high-efficient interconnection network for accelerated neuromorphic systems
X Liu, W Wen, X Qian, H Li, Y Chen
2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC), 141-146, 2018
912018
Learning low-rank deep neural networks via singular vector orthogonality regularization and singular value sparsification
H Yang, M Tang, W Wen, F Yan, D Hu, A Li, H Li, Y Chen
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
852020
A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation
C Wu, W Wen, T Afzal, Y Zhang, Y Chen, H Li
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5668-5677, 2017
702017
A novel true random number generator design leveraging emerging memristor technology
Y Wang, W Wen, H Li, M Hu
Proceedings of the 25th edition on Great Lakes Symposium on VLSI, 271-276, 2015
592015
SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning
W Wen, Y Wang, F Yan, C Xu, C Wu, Y Chen, H Li
arXiv preprint arXiv:1805.07898, 2018
58*2018
An EDA framework for large scale hybrid neuromorphic computing systems
W Wen, CR Wu, X Hu, B Liu, TY Ho, X Li, Y Chen
Proceedings of the 52nd Annual Design Automation Conference, 1-6, 2015
532015
Neuromorphic computing's yesterday, today, and tomorrow–an evolutional view
Y Chen, HH Li, C Wu, C Song, S Li, C Min, HP Cheng, W Wen, X Liu
Integration 61, 49-61, 2018
452018
Holistic sparsecnn: Forging the trident of accuracy, speed, and size
J Park, SR Li, W Wen, H Li, Y Chen, P Dubey
arXiv preprint arXiv:1608.01409 1 (2), 2016
452016
AutoGrow: Automatic Layer Growing in Deep Convolutional Networks
W Wen, F Yan, Y Chen, H Li
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2020
432020
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