Tianyun Zhang
Tianyun Zhang
Dirección de correo verificada de g.syr.edu
Citado por
Citado por
A systematic dnn weight pruning framework using alternating direction method of multipliers
T Zhang, S Ye, K Zhang, J Tang, W Wen, M Fardad, Y Wang
Proceedings of the European Conference on Computer Vision (ECCV), 184-199, 2018
Admm-nn: An algorithm-hardware co-design framework of dnns using alternating direction methods of multipliers
A Ren, T Zhang, S Ye, J Li, W Xu, X Qian, X Lin, Y Wang
Proceedings of the Twenty-Fourth International Conference on Architectural …, 2019
StructADMM: A systematic, high-efficiency framework of structured weight pruning for DNNs
T Zhang, S Ye, K Zhang, X Ma, N Liu, L Zhang, J Tang, K Ma, X Lin, ...
arXiv preprint arXiv:1807.11091, 2018
Progressive dnn compression: A key to achieve ultra-high weight pruning and quantization rates using admm
S Ye, X Feng, T Zhang, X Ma, S Lin, Z Li, K Xu, W Wen, S Liu, J Tang, ...
arXiv preprint arXiv:1903.09769, 2019
Towards a unified min-max framework for adversarial exploration and robustness
J Wang, T Zhang, S Liu, PY Chen, J Xu, M Fardad, B Li
arXiv preprint arXiv:1906.03563, 2019
ADMM-based weight pruning for real-time deep learning acceleration on mobile devices
H Li, N Liu, X Ma, S Lin, S Ye, T Zhang, X Lin, W Xu, Y Wang
Proceedings of the 2019 on Great Lakes Symposium on VLSI, 501-506, 2019
An ultra-efficient memristor-based dnn framework with structured weight pruning and quantization using admm
G Yuan, X Ma, C Ding, S Lin, T Zhang, ZS Jalali, Y Zhao, L Jiang, ...
2019 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2019
An image enhancing pattern-based sparsity for real-time inference on mobile devices
X Ma, W Niu, T Zhang, S Liu, S Lin, H Li, W Wen, X Chen, J Tang, K Ma, ...
European Conference on Computer Vision, 629-645, 2020
Computation on sparse neural networks and its implications for future hardware
F Sun, M Qin, T Zhang, L Liu, YK Chen, Y Xie
2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020
Generation of low distortion adversarial attacks via convex programming
T Zhang, S Liu, Y Wang, M Fardad
2019 IEEE International Conference on Data Mining (ICDM), 1486-1491, 2019
Reinforced adversarial attacks on deep neural networks using admm
P Zhao, K Xu, T Zhang, M Fardad, Y Wang, X Lin
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018
A unified DNN weight compression framework using reweighted optimization methods
T Zhang, X Ma, Z Zhan, S Zhou, M Qin, F Sun, YK Chen, C Ding, ...
arXiv preprint arXiv:2004.05531, 2020
BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method
X Ma, Z Li, Y Gong, T Zhang, W Niu, Z Zhan, P Zhao, J Tang, X Lin, B Ren, ...
arXiv preprint arXiv:2001.08357, 2020
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning
B Li, Z Kong, T Zhang, J Li, Z Li, H Liu, C Ding
arXiv preprint arXiv:2009.08065, 2020
On the Optimal Interdiction of Transportation Networks
T Zhang, M Fardad
2020 American Control Conference (ACC), 4701-4706, 2020
SGCN: A Graph Sparsifier Based on Graph Convolutional Networks
J Li, T Zhang, H Tian, S Jin, M Fardad, R Zafarani
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 275-287, 2020
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