Geng Yuan
Geng Yuan
Northeastern University
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CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices
C Ding, S Liao, Y Wang, Z Li, N Liu, Y Zhuo, C Wang, X Qian, Y Bai, ...
Proceedings of the 50th Annual IEEE/ACM International Symposium on …, 2017
Towards ultra-high performance and energy efficiency of deep learning systems: an algorithm-hardware co-optimization framework
Y Wang, C Ding, Z Li, G Yuan, S Liao, X Ma, B Yuan, X Qian, J Tang, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
Proposal-free temporal moment localization of a natural-language query in video using guided attention
C Rodriguez, E Marrese-Taylor, FS Saleh, H Li, S Gould
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
Structured weight matrices-based hardware accelerators in deep neural networks: Fpgas and asics
C Ding, A Ren, G Yuan, X Ma, J Li, N Liu, B Yuan, Y Wang
Proceedings of the 2018 on Great Lakes Symposium on VLSI, 353-358, 2018
An area and energy efficient design of domain-wall memory-based deep convolutional neural networks using stochastic computing
X Ma, Y Zhang, G Yuan, A Ren, Z Li, J Han, J Hu, Y Wang
2018 19th International Symposium on Quality Electronic Design (ISQED), 314-321, 2018
Tiny but accurate: A pruned, quantized and optimized memristor crossbar framework for ultra efficient dnn implementation
X Ma, G Yuan, S Lin, C Ding, F Yu, T Liu, W Wen, X Chen, Y Wang
2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), 301-306, 2020
Memristor crossbar-based ultra-efficient next-generation baseband processors
G Yuan, C Ding, R Cai, X Ma, Z Zhao, A Ren, B Yuan, Y Wang
2017 IEEE 60th International Midwest Symposium on Circuits and Systems …, 2017
Toward extremely low bit and lossless accuracy in dnns with progressive admm
S Lin, X Ma, S Ye, G Yuan, K Ma, Y Wang
arXiv preprint arXiv:1905.00789, 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
ResNet Can Be Pruned 60×: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning
X Ma, G Yuan, S Lin, Z Li, H Sun, Y Wang
2019 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH), 1-2, 2019
Non-structured DNN weight pruning considered harmful
Y Wang, S Ye, Z He, X Ma, L Zhang, S Lin, G Yuan, SH Tan, Z Li, D Fan, ...
arXiv preprint arXiv:1907.02124, 2019
Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device
P Zhao, W Niu, G Yuan, Y Cai, HH Sung, W Wen, S Liu, X Shen, B Ren, ...
arXiv preprint arXiv:2012.13801, 2020
6.7 ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration
Z Li, G Yuan, W Niu, Y Li, P Zhao, Y Cai, X Shen, Z Zhan, Z Kong, Q Jin, ...
arXiv preprint arXiv:2012.00596, 2020
An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning
C Zhang, G Yuan, W Niu, J Tian, S Jin, D Zhuang, Z Jiang, Y Wang, B Ren, ...
arXiv preprint arXiv:2011.10170, 2020
New passive and active attacks on deep neural networks in medical applications
C Gongye, H Li, X Zhang, M Sabbagh, G Yuan, X Lin, T Wahl, Y Fei
Proceedings of the 39th International Conference on Computer-Aided Design, 1-9, 2020
Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization
W Niu, Z Kong, G Yuan, W Jiang, J Guan, C Ding, P Zhao, S Liu, B Ren, ...
arXiv preprint arXiv:2009.06823, 2020
YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design
Y Cai, H Li, G Yuan, W Niu, Y Li, X Tang, B Ren, Y Wang
arXiv preprint arXiv:2009.05697, 2020
SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency
Z Li, Y Gong, X Ma, S Liu, M Sun, Z Zhan, Z Kong, G Yuan, Y Wang
arXiv preprint arXiv:2001.08839, 2020
A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation
G Yuan, X Ma, S Lin, Z Li, C Ding
arXiv preprint arXiv:1912.05416, 2019
Non-Structured DNN Weight Pruning--Is It Beneficial in Any Platform?
X Ma, S Lin, S Ye, Z He, L Zhang, G Yuan, SH Tan, Z Li, D Fan, X Qian, ...
arXiv preprint arXiv:1907.02124, 2019
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