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Yawen Wu
Yawen Wu
Qualcomm Technologies, Inc.
Verified email at nd.edu - Homepage
Title
Cited by
Cited by
Year
Positional contrastive learning for volumetric medical image segmentation
D Zeng, Y Wu, X Hu, X Xu, H Yuan, M Huang, J Zhuang, J Hu, Y Shi
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
742021
Intermittent Inference with Nonuniformly Compressed Multi-Exit Neural Network for Energy Harvesting Powered Devices
Y Wu, Z Wang, Z Jia, Y Shi, J Hu
2020 57th ACM/IEEE Design Automation Conference (DAC), 2020
582020
Federated contrastive learning for volumetric medical image segmentation
Y Wu, D Zeng, Z Wang, Y Shi, J Hu
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
542021
Enabling on-device cnn training by self-supervised instance filtering and error map pruning
Y Wu, Z Wang, Y Shi, J Hu
IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020
502020
Fairprune: Achieving fairness through pruning for dermatological disease diagnosis
Y Wu, D Zeng, X Xu, Y Shi, J Hu
International Conference on Medical Image Computing and Computer-Assisted …, 2022
342022
Distributed contrastive learning for medical image segmentation
Y Wu, D Zeng, Z Wang, Y Shi, J Hu
Medical Image Analysis 81, 102564, 2022
292022
Federated contrastive learning for dermatological disease diagnosis via on-device learning
Y Wu, D Zeng, Z Wang, Y Sheng, L Yang, AJ James, Y Shi, J Hu
2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-7, 2021
29*2021
Algorithm-hardware co-design of attention mechanism on fpga devices
X Zhang, Y Wu, P Zhou, X Tang, J Hu
ACM Transactions on Embedded Computing Systems (TECS) 20 (5s), 1-24, 2021
292021
Enabling on-device self-supervised contrastive learning with selective data contrast
Y Wu, Z Wang, D Zeng, Y Shi, J Hu
2021 58th ACM/IEEE Design Automation Conference (DAC), 655-660, 2021
25*2021
Decentralized Unsupervised Learning of Visual Representations
Y Wu, Z Wang, D Zeng, M Li, Y Shi, J Hu
Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022
202022
Lightweight run-time working memory compression for deployment of deep neural networks on resource-constrained MCUs
Z Wang, Y Wu, Z Jia, Y Shi, J Hu
Proceedings of the 26th Asia and South Pacific Design Automation Conference …, 2021
202021
The larger the fairer? small neural networks can achieve fairness for edge devices
Y Sheng, J Yang, Y Wu, K Mao, Y Shi, J Hu, W Jiang, L Yang
Proceedings of the 59th ACM/IEEE Design Automation Conference, 163-168, 2022
192022
Cooperative communication between two transiently powered sensor nodes by reinforcement learning
Y Wu, Z Jia, F Fang, J Hu
IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2021
16*2021
Developing a miniature energy-harvesting-powered edge device with multi-exit neural network
Y Li, Y Wu, X Zhang, E Hamed, J Hu, I Lee
2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021
102021
Synthetic Data Can Also Teach: Synthesizing Effective Data for Unsupervised Visual Representation Learning
Y Wu, Z Wang, D Zeng, Y Shi, J Hu
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-2023), 2023
82023
Implementation of multi-exit neural-network inferences for an image-based sensing system with energy harvesting
Y Li, Y Gao, M Shao, JT Tonecha, Y Wu, J Hu, I Lee
Journal of Low Power Electronics and Applications 11 (3), 34, 2021
82021
Prototyping energy harvesting powered systems with nonvolatile processor
Y Wu, Y Sun, Z Jia, L Zhang, Y Liu, J Hu
2018 International Symposium on Rapid System Prototyping (RSP), 49-55, 2018
82018
Energy-aware adaptive multi-exit neural network inference implementation for a millimeter-scale sensing system
Y Li, Y Wu, X Zhang, J Hu, I Lee
IEEE Transactions on Very Large Scale Integration (VLSI) Systems 30 (7), 849-859, 2022
72022
Federated self-supervised contrastive learning and masked autoencoder for dermatological disease diagnosis
Y Wu, D Zeng, Z Wang, Y Sheng, L Yang, AJ James, Y Shi, J Hu
arXiv preprint arXiv:2208.11278, 2022
62022
Self-supervised On-device Federated Learning from Unlabeled Streams
J Shi, Y Wu, D Zeng, J Tao, J Hu, Y Shi
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023
5*2023
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