|Patdnn: Achieving real-time DNN execution on mobile devices with pattern-based weight pruning|
W Niu, X Ma, S Lin, S Wang, X Qian, X Lin, Y Wang, B Ren
ASPLOS'20, 907-922, 2020
|PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices.|
X Ma, FM Guo, W Niu, X Lin, J Tang, K Ma, B Ren, Y Wang
AAAI'20, 5117-5124, 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
|Spvit: Enabling faster vision transformers via soft token pruning|
Z Kong, P Dong, X Ma, X Meng, M Sun, W Niu, X Shen, G Yuan, B Ren, ...
|DNNFusion: accelerating deep neural networks execution with advanced operator fusion|
W Niu, J Guan, Y Wang, G Agrawal, B Ren
PLDI'2021, 883-898, 2021
|RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition|
P Dong, S Wang, W Niu, C Zhang, S Lin, Z Li, Y Gong, B Ren, X Lin, ...
|Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, et al. Mest: Accurate and fast memory-economic sparse training framework on the edge|
G Yuan, X Ma, W Niu, Z Li
Advances in Neural Information Processing Systems 34 (20838-20850), 2, 2021
|Achieving on-mobile real-time super-resolution with neural architecture and pruning search|
Z Zhan, Y Gong, P Zhao, G Yuan, W Niu, Y Wu, T Zhang, M Jayaweera, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
|An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices|
X Ma, W Niu, T Zhang, S Liu, FM Guo, S Lin, H Li, X Chen, J Tang, K Ma, ...
ECCV'20: Proceedings of the European Conference on Computer Vision, 2020
|Mest: Accurate and fast memory-economic sparse training framework on the edge|
G Yuan, X Ma, W Niu, Z Li, Z Kong, N Liu, Y Gong, Z Zhan, C He, Q Jin, ...
Advances in Neural Information Processing Systems 34, 20838-20850, 2021
|26ms inference time for resnet-50: Towards real-time execution of all dnns on smartphone|
W Niu, X Ma, Y Wang, B Ren
ICML2019 workshop, 2019
|Npas: A compiler-aware framework of unified network pruning and architecture search for beyond real-time mobile acceleration|
Z Li, G Yuan, W Niu, P Zhao, Y Li, Y Cai, X Shen, Z Zhan, Z Kong, Q Jin, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
|A Privacy-Preserving DNN Pruning and Mobile Acceleration Framework|
Z Zhan, Y Gong, Z Li, P Zhao, X Ma, W Niu, X Xu, B Ren, Y Wang, X Lin
GLSVLSI '20: Proceedings of the 2020 on Great Lakes Symposium on VLSI, 2020
|SparCL: Sparse continual learning on the edge|
Z Wang, Z Zhan, Y Gong, G Yuan, W Niu, T Jian, B Ren, S Ioannidis, ...
Advances in Neural Information Processing Systems 35, 20366-20380, 2022
|Grim: A general, real-time deep learning inference framework for mobile devices based on fine-grained structured weight sparsity|
W Niu, Z Li, X Ma, P Dong, G Zhou, X Qian, X Lin, Y Wang, B Ren
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 6224 …, 2021
|CoCoPIE: Enabling real-time AI on off-the-shelf mobile devices via compression-compilation co-design|
H Guan, S Liu, X Ma, W Niu, B Ren, X Shen, Y Wang, P Zhao
Communications of the ACM 64 (6), 62-68, 2021
|Clicktrain: Efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning|
C Zhang, G Yuan, W Niu, J Tian, S Jin, D Zhuang, Z Jiang, Y Wang, B Ren, ...
Proceedings of the ACM international conference on supercomputing, 266-278, 2021
|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
|Compiler-aware neural architecture search for on-mobile real-time super-resolution|
Y Wu, Y Gong, P Zhao, Y Li, Z Zhan, W Niu, H Tang, M Qin, B Ren, ...
European Conference on Computer Vision, 92-111, 2022
|RT3D: Achieving real-time execution of 3d convolutional neural networks on mobile devices|
W Niu, M Sun, Z Li, JA Chen, J Guan, X Shen, Y Wang, S Liu, X Lin, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 9179-9187, 2021