Amc: Automl for model compression and acceleration on mobile devices Y He*, J Lin*, Z Liu, H Wang, LJ Li, S Han ECCV 2018, 784-800, 2018 | 1631 | 2018 |
Searching efficient 3d architectures with sparse point-voxel convolution H Tang, Z Liu, S Zhao, Y Lin, J Lin, H Wang, S Han ECCV 2020, 2020 | 604 | 2020 |
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing H Wang, Z Wu, Z Liu, H Cai, L Zhu, C Gan, S Han ACL 2020, 2020 | 282 | 2020 |
Spatten: Efficient sparse attention architecture with cascade token and head pruning H Wang, Z Zhang, S Han 2021 IEEE International Symposium on High-Performance Computer Architecture …, 2021 | 265 | 2021 |
GCN-RL circuit designer: Transferable transistor sizing with graph neural networks and reinforcement learning H Wang, K Wang, J Yang, L Shen, N Sun, HS Lee, S Han DAC 2020, 1-6, 2020 | 233 | 2020 |
SpArch: Efficient Architecture for Sparse Matrix Multiplication H Wang*, Z Zhang*, S Han, WJ Dally HPCA 2020, 2020 | 231 | 2020 |
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 CVPR 2020, 2020 | 205 | 2020 |
Understanding performance differences of FPGAs and GPUs J Cong*, Z Fang*, M Lo*, H Wang*, J Xu*, S Zhang* FCCM 2018, 93-96, 2018 | 160 | 2018 |
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits H Wang, Y Ding, J Gu, Y Lin, DZ Pan, FT Chong, S Han HPCA 2022, 2021 | 128 | 2021 |
Learning to Design Circuits H Wang, J Yang, HS Lee, S Han NeurIPS SysML 2018, 2018 | 101 | 2018 |
Park: An Open Platform for Learning-Augmented Computer Systems H Mao, P Negi, A Narayan, H Wang, J Yang, H Wang, R Marcus, ... NeurIPS 2019, 2490-2502, 2019 | 92 | 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 TODAES 2022 27 (3), 1-50, 2022 | 84 | 2022 |
QuantumNAT: Quantum Noise-Aware Training with Noise Injection, Quantization and Normalization H Wang, J Gu, Y Ding, Z Li, FT Chong, DZ Pan, S Han DAC 2022, 2021 | 60* | 2021 |
Pointacc: Efficient point cloud accelerator Y Lin, Z Zhang, H Tang, H Wang, S Han MICRO 2021, 449-461, 2021 | 59 | 2021 |
QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning H Wang, Z Li, J Gu, Y Ding, DZ Pan, S Han DAC 2022, 2022 | 52* | 2022 |
Variational quantum pulse learning H Wang*, Z Liang*, J Cheng, Y Ding, H Ren, X Qian, S Han, W Jiang, ... QCE 2022, 2022 | 47* | 2022 |
QuEst: Graph Transformer for Quantum Circuit Reliability Estimation H Wang, P Liu, J Cheng, Z Liang, J Gu, Z Li, Y Ding, W Jiang, Y Shi, ... ICCAD 2022, 2022 | 39* | 2022 |
NAPA: Intermediate-level Variational Native-pulse Ansatz for Variational Quantum Algorithms Z Liang, J Cheng, H Ren, H Wang, F Hua, Y Ding, F Chong, S Han, Y Shi, ... TCAD 2024, 2024 | 35* | 2024 |
DeepVS: a deep learning approach for RF-based vital signs sensing Z Xie, H Wang, S Han, E Schoenfeld, F Ye ACM-BCB 2022, 1-5, 2022 | 22 | 2022 |
SnCQA: A hardware-efficient equivariant quantum convolutional circuit architecture H Zheng, GS Ravi, H Wang, K Setia, FT Chong, J Liu QCE 2023 [Best Paper Award], 2022 | 17* | 2022 |