| Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Y Lin, S Han, H Mao, Y Wang, WJ Dally arXiv preprint arXiv:1712.01887, 2017 | 1448 | 2017 |
| HAQ: Hardware-aware Automated Quantization with Mixed Precision K Wang, Z Liu, Y Lin, J Lin, S Han Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 998 | 2019 |
| Point-Voxel CNN for Efficient 3D Deep Learning Z Liu, H Tang, Y Lin, S Han Advances in Neural Information Processing Systems 32, 2019 | 656 | 2019 |
| Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution H Tang, Z Liu, S Zhao, Y Lin, J Lin, H Wang, S Han European conference on computer vision, 685-702, 2020 | 557 | 2020 |
| MCUNet: Tiny Deep Learning on IoT Devices J Lin, WM Chen, Y Lin, C Gan, S Han Advances in Neural Information Processing Systems 33, 11711-11722, 2020 | 430 | 2020 |
| Lite Transformer with Long-Short Range Attention Z Wu, Z Liu, J Lin, Y Lin, S Han Proceedings of the International Conference on Learning Representitive (ICLR’20), 2020 | 287 | 2020 |
| Big Data Driven Mobile Traffic Understanding and Forecasting: A Time Series Approach F Xu, Y Lin, J Huang, D Wu, H Shi, J Song, Y Li IEEE transactions on services computing 9 (5), 796-805, 2016 | 257 | 2016 |
| APQ: Joint Search for Network Architecture, Pruning and Quantization Policy T Wang, K Wang, H Cai, J Lin, Z Liu, H Wang, Y Lin, S Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 194 | 2020 |
| QuantumNAS: Noise-adaptive Search for Robust Quantum Circuits H Wang, Y Ding, J Gu, Y Lin, DZ Pan, FT Chong, S Han 2022 IEEE International Symposium on High-Performance Computer Architecture …, 2022 | 116 | 2022 |
| A Configurable Multi-precision CNN Computing Framework based on Single Bit RRAM Z Zhu, H Sun, Y Lin, G Dai, L Xia, S Han, Y Wang, H Yang Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 85 | 2019 |
| Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications H Cai, J Lin, Y Lin, Z Liu, H Tang, H Wang, L Zhu, S Han ACM Transactions on Design Automation of Electronic Systems (TODAES) 27 (3 …, 2022 | 77 | 2022 |
| TorchSparse: Efficient Point Cloud Inference Engine H Tang, Z Liu, X Li, Y Lin, S Han Proceedings of Machine Learning and Systems 4, 302-315, 2022 | 73 | 2022 |
| PointAcc: Efficient Point Cloud Accelerator Y Lin, Z Zhang, H Tang, H Wang, S Han MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021 | 56 | 2021 |
| NAAS: Neural Accelerator Architecture Search Y Lin, M Yang, S Han 2021 58th ACM/IEEE Design Automation Conference (DAC), 1051-1056, 2021 | 52 | 2021 |
| Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning L Zhu, H Lin, Y Lu, Y Lin, S Han Advances in Neural Information Processing Systems 34, 29995-30007, 2021 | 50 | 2021 |
| Long Live Time: Improving Lifetime for Training-in-memory Engines by Structured Gradient Sparsification Y Cai, Y Lin, L Xia, X Chen, S Han, Y Wang, H Yang Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 50 | 2018 |
| AutoML for Architecting Efficient and Specialized Neural Networks H Cai, J Lin, Y Lin, Z Liu, K Wang, T Wang, L Zhu, S Han IEEE Micro 40 (1), 75-82, 2019 | 31 | 2019 |
| Neural-Hardware Architecture Search Y Lin, D Hafdi, K Wang, Z Liu, S Han NeurIPS Workshop on Machine Learning for Systems, 2019 | 22 | 2019 |
| Design Automation for Efficient Deep Learning Computing S Han, H Cai, L Zhu, J Lin, K Wang, Z Liu, Y Lin arXiv preprint arXiv:1904.10616, 2019 | 21 | 2019 |
| Hardware-centric AutoML for Mixed-precision Quantization K Wang, Z Liu, Y Lin, J Lin, S Han International Journal of Computer Vision 128 (8-9), 2035-2048, 2020 | 16 | 2020 |
Song HanMassachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
