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Song Han 0003
Person information
- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
- affiliation (former): Stanford University, Stanford, USA
Other persons with the same name
- Song Han — disambiguation page
- Song Han 0001
— Yanshan University, Institute of Electrical Engineering, Qinhuangdao, China
- Song Han 0002
— University of Connecticut, Department of Computer Science and Engineering, Storrs, CT, USA (and 2 more)
- Song Han 0004 — Curtin University, School of Information Systems, Perth, Australia (and 1 more)
- Song Han 0005 — Kim Il Sung University, Pyongyang, North Korea
- Song Han 0006
— Zhejiang Gongshang University, Hangzhou, Zhejiang, China (and 1 more)
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2020 – today
- 2024
- [j20]Zhiding Liang
, Jinglei Cheng
, Hang Ren
, Hanrui Wang
, Fei Hua, Zhixin Song, Yongshan Ding
, Frederic T. Chong
, Song Han
, Xuehai Qian, Yiyu Shi
:
NAPA: Intermediate-Level Variational Native-Pulse Ansatz for Variational Quantum Algorithms. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(6): 1834-1847 (2024) - [c85]Hanqing Zhu, Jiaqi Gu, Hanrui Wang, Zixuan Jiang, Zhekai Zhang, Rongxing Tang, Chenghao Feng, Song Han, Ray T. Chen, David Z. Pan:
Lightening-Transformer: A Dynamically-Operated Optically-Interconnected Photonic Transformer Accelerator. HPCA 2024: 686-703 - [c84]Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, Jiaya Jia:
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models. ICLR 2024 - [c83]Hanrui Wang, Pengyu Liu, Daniel Bochen Tan, Yilian Liu, Jiaqi Gu, David Z. Pan, Jason Cong, Umut A. Acar, Song Han:
Atomique: A Quantum Compiler for Reconfigurable Neutral Atom Arrays. ISCA 2024: 293-309 - [c82]Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, Song Han:
AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration. MLSys 2024 - [i88]Tianlong Chen, Zhenyu Zhang, Hanrui Wang, Jiaqi Gu, Zirui Li, David Z. Pan, Frederic T. Chong, Song Han, Zhangyang Wang:
QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits. CoRR abs/2401.05571 (2024) - [i87]Junyao Zhang, Hanrui Wang, Qi Ding, Jiaqi Gu, Reouven Assouly, William D. Oliver, Song Han, Kenneth R. Brown, Hai Helen Li, Yiran Chen:
Qplacer: Frequency-Aware Component Placement for Superconducting Quantum Computers. CoRR abs/2401.17450 (2024) - [i86]Zhuoyang Zhang, Han Cai, Song Han:
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss. CoRR abs/2402.05008 (2024) - [i85]James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai:
BitDelta: Your Fine-Tune May Only Be Worth One Bit. CoRR abs/2402.10193 (2024) - [i84]Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Ming-Yu Liu, Kai Li, Song Han:
DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models. CoRR abs/2402.19481 (2024) - [i83]Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Song Han:
Tiny Machine Learning: Progress and Futures. CoRR abs/2403.19076 (2024) - [i82]Yujun Lin, Haotian Tang, Shang Yang, Zhekai Zhang, Guangxuan Xiao, Chuang Gan, Song Han:
QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving. CoRR abs/2405.04532 (2024) - [i81]Zhijian Liu, Zhuoyang Zhang, Samir Khaki, Shang Yang, Haotian Tang, Chenfeng Xu, Kurt Keutzer, Song Han:
Sparse Refinement for Efficient High-Resolution Semantic Segmentation. CoRR abs/2407.19014 (2024) - 2023
- [j19]Muyang Li
, Ji Lin
, Chenlin Meng
, Stefano Ermon
, Song Han
, Jun-Yan Zhu
:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14465-14480 (2023) - [j18]Zhijian Liu
, Haotian Tang
, Yujun Lin
, Song Han
:
Algorithm-System-Hardware Co-Design for Efficient 3D Deep Learning. World Sci. Annu. Rev. Artif. Intell. 1: 2340003:1-2340003:56 (2023) - [c81]Jessica Zheng, Hanrui Wang, Anand Chandrasekhar, Aaron D. Aguirre, Song Han, Hae-Seung Lee, Charles G. Sodini:
Machine Learning for Arterial Blood Pressure Prediction. CHIL 2023: 427-439 - [c80]Haotian Tang, Shang Yang, Zhijian Liu, Ke Hong, Zhongming Yu, Xiuyu Li, Guohao Dai, Yu Wang, Song Han:
TorchSparse++: Efficient Point Cloud Engine. CVPR Workshops 2023: 202-209 - [c79]Zhijian Liu, Xinyu Yang, Haotian Tang, Shang Yang, Song Han:
FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer. CVPR 2023: 1200-1211 - [c78]Xuanyao Chen, Zhijian Liu, Haotian Tang, Li Yi, Hang Zhao, Song Han:
SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer. CVPR 2023: 2061-2070 - [c77]Zhiding Liang, Zhixin Song, Jinglei Cheng, Zichang He, Ji Liu, Hanrui Wang, Ruiyang Qin, Yiru Wang, Song Han, Xuehai Qian, Yiyu Shi:
Hybrid Gate-Pulse Model for Variational Quantum Algorithms. DAC 2023: 1-6 - [c76]Sanjay Deshpande, Chuanqi Xu, Theodoros Trochatos, Hanrui Wang, Ferhat Erata, Song Han, Yongshan Ding
, Jakub Szefer:
Design of Quantum Computer Antivirus. HOST 2023: 260-270 - [c75]Han Cai, Junyan Li, Muyan Hu, Chuang Gan, Song Han:
EfficientViT: Lightweight Multi-Scale Attention for High-Resolution Dense Prediction. ICCV 2023: 17256-17267 - [c74]Guangxuan Xiao, Ji Lin, Mickaël Seznec, Hao Wu, Julien Demouth, Song Han:
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. ICML 2023: 38087-38099 - [c73]Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela L. Rus, Song Han:
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation. ICRA 2023: 2774-2781 - [c72]Zexi Ji, Hanrui Wang, Miaorong Wang, Win-San Khwa, Meng-Fan Chang, Song Han, Anantha P. Chandrakasan:
A Fully-Integrated Energy-Scalable Transformer Accelerator Supporting Adaptive Model Configuration and Word Elimination for Language Understanding on Edge Devices. ISLPED 2023: 1-6 - [c71]Haotian Tang
, Shang Yang
, Zhijian Liu
, Ke Hong
, Zhongming Yu
, Xiuyu Li
, Guohao Dai
, Yu Wang
, Song Han
:
TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs. MICRO 2023: 225-239 - [c70]Ligeng Zhu
, Lanxiang Hu
, Ji Lin
, Wei-Ming Chen
, Wei-Chen Wang
, Chuang Gan
, Song Han
:
PockEngine: Sparse and Efficient Fine-tuning in a Pocket. MICRO 2023: 1381-1394 - [c69]Tianlong Chen, Zhenyu Zhang, Hanrui Wang, Jiaqi Gu, Zirui Li, David Z. Pan, Frederic T. Chong, Song Han, Zhangyang Wang:
QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits. QCE 2023: 51-62 - [c68]Junyao Zhang, Hanrui Wang, Gokul Subramanian Ravi, Frederic T. Chong, Song Han, Frank Mueller, Yiran Chen:
DISQ: Dynamic Iteration Skipping for Variational Quantum Algorithms. QCE 2023: 1062-1073 - [i80]Zhijian Liu, Xinyu Yang, Haotian Tang, Shang Yang, Song Han:
FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer. CoRR abs/2301.08739 (2023) - [i79]Guangxuan Xiao, Ji Lin, Song Han:
Offsite-Tuning: Transfer Learning without Full Model. CoRR abs/2302.04870 (2023) - [i78]Xuanyao Chen, Zhijian Liu, Haotian Tang, Li Yi, Hang Zhao, Song Han:
SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer. CoRR abs/2303.17605 (2023) - [i77]Hanqing Zhu, Jiaqi Gu, Hanrui Wang, Zixuan Jiang, Zhekai Zhang, Rongxin Tang, Chenghao Feng, Song Han, Ray T. Chen, David Z. Pan:
DOTA: A Dynamically-Operated Photonic Tensor Core for Energy-Efficient Transformer Accelerator. CoRR abs/2305.19533 (2023) - [i76]Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Xingyu Dang, Song Han:
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. CoRR abs/2306.00978 (2023) - [i75]Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark A. Horowitz, William J. Dally:
Retrospective: EIE: Efficient Inference Engine on Sparse and Compressed Neural Network. CoRR abs/2306.09552 (2023) - [i74]Junyao Zhang, Hanrui Wang, Gokul Subramanian Ravi, Frederic T. Chong, Song Han, Frank Mueller, Yiran Chen:
DISQ: Dynamic Iteration Skipping for Variational Quantum Algorithms. CoRR abs/2308.06634 (2023) - [i73]Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, Jiaya Jia:
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models. CoRR abs/2309.12307 (2023) - [i72]Ligeng Zhu, Lanxiang Hu, Ji Lin, Wei-Chen Wang, Wei-Ming Chen, Chuang Gan, Song Han:
PockEngine: Sparse and Efficient Fine-tuning in a Pocket. CoRR abs/2310.17752 (2023) - [i71]Haotian Tang, Shang Yang, Zhijian Liu, Ke Hong, Zhongming Yu, Xiuyu Li, Guohao Dai, Yu Wang, Song Han:
TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs. CoRR abs/2311.12862 (2023) - [i70]Hanrui Wang, Pengyu Liu, Bochen Tan, Yilian Liu, Jiaqi Gu, David Z. Pan, Jason Cong, Umut A. Acar, Song Han:
FPQA-C: A Compilation Framework for Field Programmable Qubit Array. CoRR abs/2311.15123 (2023) - [i69]Hanrui Wang, Yilian Liu, Pengyu Liu, Jiaqi Gu, Zirui Li, Zhiding Liang, Jinglei Cheng, Yongshan Ding, Xuehai Qian, Yiyu Shi, David Z. Pan, Frederic T. Chong, Song Han:
RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training. CoRR abs/2311.16035 (2023) - [i68]Hanrui Wang, Pengyu Liu, Kevin Shao, Dantong Li, Jiaqi Gu, David Z. Pan, Yongshan Ding, Song Han:
Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers. CoRR abs/2311.16082 (2023) - [i67]Hanrui Wang, Bochen Tan, Pengyu Liu, Yilian Liu, Jiaqi Gu, Jason Cong, Song Han:
Q-Pilot: Field Programmable Quantum Array Compilation with Flying Ancillas. CoRR abs/2311.16190 (2023) - [i66]Hanrui Wang, Pengyu Liu, Yilian Liu, Jiaqi Gu, Jonathan M. Baker, Frederic T. Chong, Song Han:
DGR: Tackling Drifted and Correlated Noise in Quantum Error Correction via Decoding Graph Re-weighting. CoRR abs/2311.16214 (2023) - 2022
- [j17]Ji Lin
, Chuang Gan
, Kuan Wang, Song Han
:
TSM: Temporal Shift Module for Efficient and Scalable Video Understanding on Edge Devices. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2760-2774 (2022) - [j16]Zhijian Liu
, Haotian Tang, Shengyu Zhao, Kevin Shao
, Song Han
:
PVNAS: 3D Neural Architecture Search With Point-Voxel Convolution. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 8552-8568 (2022) - [j15]Muyang Li
, Ji Lin
, Yaoyao Ding, Zhijian Liu
, Jun-Yan Zhu
, Song Han
:
GAN Compression: Efficient Architectures for Interactive Conditional GANs. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9331-9346 (2022) - [j14]Han Cai, Ji Lin, Yujun Lin, Zhijian Liu, Haotian Tang, Hanrui Wang, Ligeng Zhu, Song Han:
Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications. ACM Trans. Design Autom. Electr. Syst. 27(3): 20:1-20:50 (2022) - [c67]Zongxing Xie, Hanrui Wang, Song Han, Elinor Schoenfeld, Fan Ye:
DeepVS: a deep learning approach for RF-based vital signs sensing. BCB 2022: 17:1-17:5 - [c66]Yihan Wang, Muyang Li, Han Cai, Wei-Ming Chen, Song Han:
Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation. CVPR 2022: 13116-13126 - [c65]Hanrui Wang, Jiaqi Gu, Yongshan Ding
, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han:
QuantumNAT: quantum noise-aware training with noise injection, quantization and normalization. DAC 2022: 1-6 - [c64]Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding
, David Z. Pan, Song Han:
QOC: quantum on-chip training with parameter shift and gradient pruning. DAC 2022: 655-660 - [c63]Hanrui Wang, Yongshan Ding
, Jiaqi Gu, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han:
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits. HPCA 2022: 692-708 - [c62]Hanrui Wang, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding
, Weiwen Jiang, Yiyu Shi, David Z. Pan, Frederic T. Chong, Song Han:
TorchQuantum Case Study for Robust Quantum Circuits. ICCAD 2022: 136:1-136:9 - [c61]Han Cai, Chuang Gan, Ji Lin, Song Han:
Network Augmentation for Tiny Deep Learning. ICLR 2022 - [c60]Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, Daniela Rus:
VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles. ICRA 2022: 2419-2426 - [c59]Wei Shi, Hanrui Wang, Jiaqi Gu, Mingjie Liu, David Z. Pan, Song Han, Nan Sun:
RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL. MLCAD 2022: 35-41 - [c58]Haotian Tang, Zhijian Liu, Xiuyu Li, Yujun Lin, Song Han:
TorchSparse: Efficient Point Cloud Inference Engine. MLSys 2022 - [c57]Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han:
On-Device Training Under 256KB Memory. NeurIPS 2022 - [c56]Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. NeurIPS 2022 - [c55]Zhiding Liang
, Hanrui Wang, Jinglei Cheng, Yongshan Ding
, Hang Ren, Zhengqi Gao, Zhirui Hu, Duane S. Boning, Xuehai Qian, Song Han, Weiwen Jiang, Yiyu Shi:
Variational Quantum Pulse Learning. QCE 2022: 556-565 - [i65]Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han:
On-chip QNN: Towards Efficient On-Chip Training of Quantum Neural Networks. CoRR abs/2202.13239 (2022) - [i64]Haotian Tang, Zhijian Liu, Xiuyu Li, Yujun Lin, Song Han:
TorchSparse: Efficient Point Cloud Inference Engine. CoRR abs/2204.10319 (2022) - [i63]Han Cai, Ji Lin, Yujun Lin, Zhijian Liu, Haotian Tang, Hanrui Wang, Ligeng Zhu, Song Han:
Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications. CoRR abs/2204.11786 (2022) - [i62]Zhijian Liu, Haotian Tang, Shengyu Zhao, Kevin Shao, Song Han:
PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution. CoRR abs/2204.11797 (2022) - [i61]Yihan Wang, Muyang Li, Han Cai, Wei-Ming Chen, Song Han:
Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation. CoRR abs/2205.01271 (2022) - [i60]Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela Rus, Song Han:
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation. CoRR abs/2205.13542 (2022) - [i59]Han Cai, Chuang Gan, Song Han:
EfficientViT: Enhanced Linear Attention for High-Resolution Low-Computation Visual Recognition. CoRR abs/2205.14756 (2022) - [i58]Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han:
On-Device Training Under 256KB Memory. CoRR abs/2206.15472 (2022) - [i57]Wei Shi, Hanrui Wang, Jiaqi Gu, Mingjie Liu, David Z. Pan, Song Han, Nan Sun:
RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL. CoRR abs/2207.06412 (2022) - [i56]Zhiding Liang, Jinglei Cheng, Hang Ren, Hanrui Wang, Fei Hua, Yongshan Ding
, Fred Chong, Song Han, Yiyu Shi, Xuehai Qian:
PAN: Pulse Ansatz on NISQ Machines. CoRR abs/2208.01215 (2022) - [i55]Jinglei Cheng, Hanrui Wang, Zhiding Liang, Yiyu Shi, Song Han, Xuehai Qian:
TopGen: Topology-Aware Bottom-Up Generator for Variational Quantum Circuits. CoRR abs/2210.08190 (2022) - [i54]Hanrui Wang, Pengyu Liu, Jinglei Cheng, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding
, Weiwen Jiang, Yiyu Shi, Xuehai Qian, David Z. Pan, Frederic T. Chong, Song Han:
QuEst: Graph Transformer for Quantum Circuit Reliability Estimation. CoRR abs/2210.16724 (2022) - [i53]Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. CoRR abs/2211.02048 (2022) - [i52]Guangxuan Xiao, Ji Lin, Mickaël Seznec, Julien Demouth, Song Han:
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. CoRR abs/2211.10438 (2022) - [i51]Zhiding Liang, Zhixin Song, Jinglei Cheng, Zichang He, Ji Liu, Hanrui Wang, Ruiyang Qin, Yiru Wang, Song Han, Xuehai Qian, Yiyu Shi:
Hybrid Gate-Pulse Model for Variational Quantum Algorithms. CoRR abs/2212.00661 (2022) - 2021
- [c54]Xiao Hu
, Ming-Ching Chang, Yuwei Chen, Rahul Sridhar, Zhenyu Hu, Yunhe Xue, Zhenyu Wu, Pengcheng Pi, Jiayi Shen, Jianchao Tan, Xiangru Lian, Ji Liu, Zhangyang Wang, Chia-Hsiang Liu, Yu-Shin Han, Yuan-Yao Sung, Yi Lee, Kai-Chiang Wu, Wei-Xiang Guo, Rick Lee, Shengwen Liang, Zerun Wang, Guiguang Ding, Gang Zhang, Teng Xi, Yubei Chen, Han Cai, Ligeng Zhu, Zhekai Zhang, Song Han, Seonghwan Jeong, YoungMin Kwon, Tianzhe Wang, Jeffery Pan:
The 2020 Low-Power Computer Vision Challenge. AICAS 2021: 1-4 - [c53]Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zhu:
Anycost GANs for Interactive Image Synthesis and Editing. CVPR 2021: 14986-14996 - [c52]Yujun Lin, Mengtian Yang, Song Han:
NAAS: Neural Accelerator Architecture Search. DAC 2021: 1051-1056 - [c51]Hanrui Wang, Zhekai Zhang, Song Han:
SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning. HPCA 2021: 97-110 - [c50]Zhijian Liu, Simon Stent, Jie Li, John Gideon, Song Han:
LocTex: Learning Data-Efficient Visual Representations from Localized Textual Supervision. ICCV 2021: 2147-2156 - [c49]Zhijian Liu, Alexander Amini, Sibo Zhu, Sertac Karaman, Song Han, Daniela L. Rus:
Efficient and Robust LiDAR-Based End-to-End Navigation. ICRA 2021: 13247-13254 - [c48]Zhijian Liu, Haotian Tang, Sibo Zhu, Song Han:
SemAlign: Annotation-Free Camera-LiDAR Calibration with Semantic Alignment Loss. IROS 2021: 8845-8851 - [c47]Yujun Lin
, Zhekai Zhang, Haotian Tang, Hanrui Wang, Song Han:
PointAcc: Efficient Point Cloud Accelerator. MICRO 2021: 449-461 - [c46]Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han:
IOS: Inter-Operator Scheduler for CNN Acceleration. MLSys 2021 - [c45]Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han:
Memory-efficient Patch-based Inference for Tiny Deep Learning. NeurIPS 2021: 2346-2358 - [c44]Ligeng Zhu, Hongzhou Lin, Yao Lu, Yujun Lin, Song Han:
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning. NeurIPS 2021: 29995-30007 - [i50]Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zhu:
Anycost GANs for Interactive Image Synthesis and Editing. CoRR abs/2103.03243 (2021) - [i49]Huizi Mao, Sibo Zhu, Song Han, William J. Dally:
PatchNet - Short-range Template Matching for Efficient Video Processing. CoRR abs/2103.07371 (2021) - [i48]Zhijian Liu, Alexander Amini, Sibo Zhu, Sertac Karaman, Song Han, Daniela Rus:
Efficient and Robust LiDAR-Based End-to-End Navigation. CoRR abs/2105.09932 (2021) - [i47]Yujun Lin, Mengtian Yang, Song Han:
NAAS: Neural Accelerator Architecture Search. CoRR abs/2105.13258 (2021) - [i46]Hanrui Wang, Yongshan Ding, Jiaqi Gu, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han:
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits. CoRR abs/2107.10845 (2021) - [i45]Zhijian Liu, Simon Stent, Jie Li, John Gideon, Song Han:
LocTex: Learning Data-Efficient Visual Representations from Localized Textual Supervision. CoRR abs/2108.11950 (2021) - [i44]Ji Lin, Chuang Gan, Kuan Wang, Song Han:
TSM: Temporal Shift Module for Efficient and Scalable Video Understanding on Edge Device. CoRR abs/2109.13227 (2021) - [i43]Yujun Lin, Zhekai Zhang, Haotian Tang, Hanrui Wang, Song Han:
PointAcc: Efficient Point Cloud Accelerator. CoRR abs/2110.07600 (2021) - [i42]Han Cai, Chuang Gan, Ji Lin, Song Han:
Network Augmentation for Tiny Deep Learning. CoRR abs/2110.08890 (2021) - [i41]Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han:
RoQNN: Noise-Aware Training for Robust Quantum Neural Networks. CoRR abs/2110.11331 (2021) - [i40]Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han:
MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning. CoRR abs/2110.15352 (2021) - [i39]Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, Daniela Rus:
VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles. CoRR abs/2111.12083 (2021) - 2020
- [j13]William J. Dally, Yatish Turakhia, Song Han:
Domain-specific hardware accelerators. Commun. ACM 63(7): 48-57 (2020) - [j12]Kuan Wang, Zhijian Liu, Yujun Lin
, Ji Lin, Song Han
:
Hardware-Centric AutoML for Mixed-Precision Quantization. Int. J. Comput. Vis. 128(8): 2035-2048 (2020) - [j11]Han Cai, Ji Lin, Yujun Lin
, Zhijian Liu, Kuan Wang, Tianzhe Wang, Ligeng Zhu, Song Han:
AutoML for Architecting Efficient and Specialized Neural Networks. IEEE Micro 40(1): 75-82 (2020) - [j10]H.-S. Philip Wong, Kerem Akarvardar, Dimitri A. Antoniadis, Jeffrey Bokor, Chenming Hu, Tsu-Jae King Liu, Subhasish Mitra, James D. Plummer, Sayeef S. Salahuddin, Lei Deng, Xin-Guo Li, Song Han, Luping Shi, Yuan Xie, Elias Yaacoub, Mohamed-Slim Alouini, Ahmed Douik, Hayssam Dahrouj, Tareq Y. Al-Naffouri:
Scanning the Issue. Proc. IEEE 108(4): 483-484 (2020) - [j9]Lei Deng
, Guoqi Li
, Song Han
, Luping Shi
, Yuan Xie:
Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey. Proc. IEEE 108(4): 485-532 (2020) - [j8]Milad Mohammadi
, Song Han, Ehsan Atoofian
, Amirali Baniasadi, Tor M. Aamodt, William J. Dally:
Energy Efficient On-Demand Dynamic Branch Prediction Models. IEEE Trans. Computers 69(3): 453-465 (2020) - [j7]Yi Cai
, Yujun Lin
, Lixue Xia, Xiaoming Chen
, Song Han
, Yu Wang
, Huazhong Yang
:
Long Live TIME: Improving Lifetime and Security for NVM-Based Training-in-Memory Systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(12): 4707-4720 (2020) - [c43]Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han:
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing. ACL 2020: 7675-7688 - [c42]Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Hanrui Wang, Yujun Lin
, Song Han:
APQ: Joint Search for Network Architecture, Pruning and Quantization Policy. CVPR 2020: 2075-2084 - [c41]Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han:
GAN Compression: Efficient Architectures for Interactive Conditional GANs. CVPR 2020: 5283-5293 - [c40]Hanrui Wang, Kuan Wang, Jiacheng Yang
, Linxiao Shen, Nan Sun, Hae-Seung Lee, Song Han:
GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning. DAC 2020: 1-6 - [c39]Zhijian Liu, Zhanghao Wu, Chuang Gan, Ligeng Zhu, Song Han:
DataMix: Efficient Privacy-Preserving Edge-Cloud Inference. ECCV (11) 2020: 578-595 - [c38]Haotian Tang, Zhijian Liu, Shengyu Zhao, Yujun Lin
, Ji Lin, Hanrui Wang, Song Han:
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution. ECCV (28) 2020: 685-702 - [c37]Zhekai Zhang, Hanrui Wang, Song Han, William J. Dally:
SpArch: Efficient Architecture for Sparse Matrix Multiplication. HPCA 2020: 261-274 - [c36]Han Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang, Song Han:
Once-for-All: Train One Network and Specialize it for Efficient Deployment. ICLR 2020 - [c35]Zhanghao Wu, Zhijian Liu, Ji Lin, Yujun Lin, Song Han:
Lite Transformer with Long-Short Range Attention. ICLR 2020 - [c34]Han Cai, Chuang Gan, Ligeng Zhu, Song Han:
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning. NeurIPS 2020 - [c33]Ji Lin, Wei-Ming Chen, Yujun Lin, John Cohn, Chuang Gan, Song Han:
MCUNet: Tiny Deep Learning on IoT Devices. NeurIPS 2020 - [c32]Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han:
Differentiable Augmentation for Data-Efficient GAN Training. NeurIPS 2020 - [p1]Ligeng Zhu, Song Han:
Deep Leakage from Gradients. Federated Learning 2020: 17-31 - [i38]Zhekai Zhang, Hanrui Wang, Song Han, William J. Dally:
SpArch: Efficient Architecture for Sparse Matrix Multiplication. CoRR abs/2002.08947 (2020) - [i37]Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han:
GAN Compression: Efficient Architectures for Interactive Conditional GANs. CoRR abs/2003.08936 (2020) - [i36]Zhanghao Wu, Zhijian Liu, Ji Lin, Yujun Lin
, Song Han:
Lite Transformer with Long-Short Range Attention. CoRR abs/2004.11886 (2020) - [i35]Hanrui Wang, Kuan Wang, Jiacheng Yang, Linxiao Shen, Nan Sun, Hae-Seung Lee, Song Han:
GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning. CoRR abs/2005.00406 (2020) - [i34]Zhongxia Yan, Hanrui Wang, Demi Guo, Song Han:
MicroNet for Efficient Language Modeling. CoRR abs/2005.07877 (2020) - [i33]Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han:
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing. CoRR abs/2005.14187 (2020) - [i32]Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Song Han:
APQ: Joint Search for Network Architecture, Pruning and Quantization Policy. CoRR abs/2006.08509 (2020) - [i31]Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han:
Differentiable Augmentation for Data-Efficient GAN Training. CoRR abs/2006.10738 (2020) - [i30]Ji Lin, Wei-Ming Chen, Yujun Lin
, John Cohn, Chuang Gan, Song Han:
MCUNet: Tiny Deep Learning on IoT Devices. CoRR abs/2007.10319 (2020) - [i29]Han Cai, Chuang Gan, Ligeng Zhu, Song Han:
Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning. CoRR abs/2007.11622 (2020) - [i28]Haotian Tang, Zhijian Liu, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, Song Han:
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution. CoRR abs/2007.16100 (2020) - [i27]Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han:
Hardware-Centric AutoML for Mixed-Precision Quantization. CoRR abs/2008.04878 (2020) - [i26]Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han:
IOS: Inter-Operator Scheduler for CNN Acceleration. CoRR abs/2011.01302 (2020) - [i25]Hanrui Wang, Zhekai Zhang, Song Han:
SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning. CoRR abs/2012.09852 (2020)
2010 – 2019
- 2019
- [j6]Chen Pan
, Mimi Xie, Song Han, Zhi-Hong Mao, Jingtong Hu:
Modeling and Optimization for Self-powered Non-volatile IoT Edge Devices with Ultra-low Harvesting Power. ACM Trans. Cyber Phys. Syst. 3(3): 32:1-32:26 (2019) - [c31]Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han:
HAQ: Hardware-Aware Automated Quantization With Mixed Precision. CVPR 2019: 8612-8620 - [c30]Zhenhua Zhu, Hanbo Sun, Yujun Lin
, Guohao Dai, Lixue Xia, Song Han, Yu Wang, Huazhong Yang:
A Configurable Multi-Precision CNN Computing Framework Based on Single Bit RRAM. DAC 2019: 56 - [c29]Shulin Zeng, Yujun Lin
, Shuang Liang, Junlong Kang, Dongliang Xie, Yi Shan, Song Han, Yu Wang, Huazhong Yang:
A Fine-Grained Sparse Accelerator for Multi-Precision DNN. FPGA 2019: 185 - [c28]Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Dylan S. Rankin, Ryan A. Rivera, Sioni Summers, Nhan Tran, Zhenbin Wu:
Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. FPGA 2019: 305 - [c27]Ji Lin, Chuang Gan, Song Han:
TSM: Temporal Shift Module for Efficient Video Understanding. ICCV 2019: 7082-7092 - [c26]Han Cai, Tianzhe Wang, Zhanghao Wu, Kuan Wang, Ji Lin, Song Han:
On-Device Image Classification with Proxyless Neural Architecture Search and Quantization-Aware Fine-Tuning. ICCV Workshops 2019: 2509-2513 - [c25]Han Cai, Ligeng Zhu, Song Han:
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. ICLR (Poster) 2019 - [c24]Ji Lin, Chuang Gan, Song Han:
Defensive Quantization: When Efficiency Meets Robustness. ICLR (Poster) 2019 - [c23]Zhongxia Yan, Hanrui Wang, Demi Guo, Song Han:
MicroNet for Efficient Language Modeling. NeurIPS (Competition and Demos) 2019: 215-231 - [c22]Zhijian Liu, Haotian Tang, Yujun Lin, Song Han:
Point-Voxel CNN for Efficient 3D Deep Learning. NeurIPS 2019: 963-973 - [c21]Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Bojja Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Mohammad Alizadeh:
Park: An Open Platform for Learning-Augmented Computer Systems. NeurIPS 2019: 2490-2502 - [c20]Ligeng Zhu, Zhijian Liu, Song Han:
Deep Leakage from Gradients. NeurIPS 2019: 14747-14756 - [i24]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li
, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i23]Ji Lin, Chuang Gan, Song Han:
Defensive Quantization: When Efficiency Meets Robustness. CoRR abs/1904.08444 (2019) - [i22]Song Han, Han Cai, Ligeng Zhu, Ji Lin, Kuan Wang, Zhijian Liu, Yujun Lin:
Design Automation for Efficient Deep Learning Computing. CoRR abs/1904.10616 (2019) - [i21]Ligeng Zhu, Zhijian Liu, Song Han:
Deep Leakage from Gradients. CoRR abs/1906.08935 (2019) - [i20]Zhijian Liu, Haotian Tang, Yujun Lin
, Song Han:
Point-Voxel CNN for Efficient 3D Deep Learning. CoRR abs/1907.03739 (2019) - [i19]Han Cai, Chuang Gan, Song Han:
Once for All: Train One Network and Specialize it for Efficient Deployment. CoRR abs/1908.09791 (2019) - [i18]Ji Lin, Chuang Gan, Song Han:
Training Kinetics in 15 Minutes: Large-scale Distributed Training on Videos. CoRR abs/1910.00932 (2019) - 2018
- [j5]Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Jincheng Yu, Junbin Wang, Song Yao, Song Han, Yu Wang
, Huazhong Yang:
Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(1): 35-47 (2018) - [c19]Yi Cai, Yujun Lin
, Lixue Xia, Xiaoming Chen, Song Han, Yu Wang, Huazhong Yang:
Long live TIME: improving lifetime for training-in-memory engines by structured gradient sparsification. DAC 2018: 107:1-107:6 - [c18]Song Han, William J. Dally:
Bandwidth-efficient deep learning. DAC 2018: 147:1-147:6 - [c17]Yihui He, Ji Lin, Zhijian Liu, Hanrui Wang, Li-Jia Li
, Song Han:
AMC: AutoML for Model Compression and Acceleration on Mobile Devices. ECCV (7) 2018: 815-832 - [c16]Yujun Lin, Song Han, Huizi Mao, Yu Wang, Bill Dally:
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training. ICLR (Poster) 2018 - [c15]Xingyu Liu, Jeff Pool, Song Han, William J. Dally:
Efficient Sparse-Winograd Convolutional Neural Networks. ICLR (Poster) 2018 - [c14]Han Cai, Jiacheng Yang, Weinan Zhang, Song Han, Yong Yu:
Path-Level Network Transformation for Efficient Architecture Search. ICML 2018: 677-686 - [i17]Xingyu Liu, Jeff Pool, Song Han, William J. Dally:
Efficient Sparse-Winograd Convolutional Neural Networks. CoRR abs/1802.06367 (2018) - [i16]Javier M. Duarte
, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Jennifer Ngadiuba
, Maurizio Pierini, Ryan A. Rivera, Nhan Tran, Zhenbin Wu:
Fast inference of deep neural networks in FPGAs for particle physics. CoRR abs/1804.06913 (2018) - [i15]Han Cai, Jiacheng Yang, Weinan Zhang, Song Han, Yong Yu:
Path-Level Network Transformation for Efficient Architecture Search. CoRR abs/1806.02639 (2018) - [i14]Ji Lin, Chuang Gan, Song Han:
Temporal Shift Module for Efficient Video Understanding. CoRR abs/1811.08383 (2018) - [i13]Kuan Wang, Zhijian Liu, Yujun Lin
, Ji Lin, Song Han:
HAQ: Hardware-Aware Automated Quantization. CoRR abs/1811.08886 (2018) - [i12]Han Cai, Ligeng Zhu, Song Han:
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. CoRR abs/1812.00332 (2018) - [i11]Hanrui Wang, Jiacheng Yang, Hae-Seung Lee, Song Han:
Learning to Design Circuits. CoRR abs/1812.02734 (2018) - 2017
- [j4]Peter Bailis, Arvind Narayanan, Andrew Miller, Song Han:
Research for practice: cryptocurrencies, blockchains, and smart contracts; hardware for deep learning. Commun. ACM 60(5): 48-51 (2017) - [j3]Kaiyuan Guo, Song Han, Song Yao, Yu Wang, Yuan Xie, Huazhong Yang:
Software-Hardware Codesign for Efficient Neural Network Acceleration. IEEE Micro 37(2): 18-25 (2017) - [c13]Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J. Dally:
Exploring the Granularity of Sparsity in Convolutional Neural Networks. CVPR Workshops 2017: 1927-1934 - [c12]Sicheng Li, Wei Wen, Yu Wang, Song Han, Yiran Chen, Hai Li
:
An FPGA Design Framework for CNN Sparsification and Acceleration. FCCM 2017: 28 - [c11]Song Han, Junlong Kang, Huizi Mao, Yiming Hu, Xin Li, Yubin Li, Dongliang Xie, Hong Luo, Song Yao, Yu Wang, Huazhong Yang, William (Bill) J. Dally:
ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA. FPGA 2017: 75-84 - [c10]Song Han, Jeff Pool, Sharan Narang, Huizi Mao, Enhao Gong, Shijian Tang, Erich Elsen, Peter Vajda, Manohar Paluri, John Tran, Bryan Catanzaro, William J. Dally:
DSD: Dense-Sparse-Dense Training for Deep Neural Networks. ICLR (Poster) 2017 - [c9]Xingyu Liu, Song Han, Huizi Mao, William J. Dally:
Efficient Sparse-Winograd Convolutional Neural Networks. ICLR (Workshop) 2017 - [c8]Chenzhuo Zhu, Song Han, Huizi Mao, William J. Dally:
Trained Ternary Quantization. ICLR (Poster) 2017 - [i10]Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J. Dally:
Exploring the Regularity of Sparse Structure in Convolutional Neural Networks. CoRR abs/1705.08922 (2017) - [i9]Morteza Mardani, Enhao Gong, Joseph Y. Cheng, Shreyas Vasanawala, Greg Zaharchuk, Marcus T. Alley, Neil Thakur, Song Han, William J. Dally, John M. Pauly, Lei Xing:
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI. CoRR abs/1706.00051 (2017) - [i8]Yujun Lin
, Song Han, Huizi Mao, Yu Wang, William J. Dally:
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training. CoRR abs/1712.01887 (2017) - 2016
- [j2]Peter Bailis, Arvind Narayanan, Andrew Miller, Song Han:
Research for Practice: Cryptocurrencies, Blockchains, and Smart Contracts; Hardware for Deep Learning. ACM Queue 14(6): 43-55 (2016) - [c7]Junbin Wang, Ke Yan, Kaiyuan Guo, Jincheng Yu, Lingzhi Sui, Song Yao, Song Han, Yu Wang:
Real-Time Pedestrian Detection and Tracking on Customized Hardware. ESTIMedia 2016: 1 - [c6]Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Song Yao, Song Han, Yu Wang, Huazhong Yang:
From model to FPGA: Software-hardware co-design for efficient neural network acceleration. Hot Chips Symposium 2016: 1-27 - [c5]Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark Horowitz, Bill Dally:
Deep compression and EIE: Efficient inference engine on compressed deep neural network. Hot Chips Symposium 2016: 1-6 - [c4]Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark A. Horowitz, William J. Dally:
EIE: Efficient Inference Engine on Compressed Deep Neural Network. ISCA 2016: 243-254 - [c3]Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Song Yao, Song Han, Yu Wang, Huazhong Yang:
Angel-Eye: A Complete Design Flow for Mapping CNN onto Customized Hardware. ISVLSI 2016: 24-29 - [c2]Song Han, Huizi Mao, William J. Dally:
Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding. ICLR 2016 - [i7]Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark A. Horowitz, William J. Dally:
EIE: Efficient Inference Engine on Compressed Deep Neural Network. CoRR abs/1602.01528 (2016) - [i6]Shijian Tang, Song Han:
Generate Image Descriptions based on Deep RNN and Memory Cells for Images Features. CoRR abs/1602.01895 (2016) - [i5]Forrest N. Iandola, Matthew W. Moskewicz, Khalid Ashraf, Song Han, William J. Dally, Kurt Keutzer:
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size. CoRR abs/1602.07360 (2016) - [i4]Song Han, Jeff Pool, Sharan Narang, Huizi Mao, Shijian Tang, Erich Elsen, Bryan Catanzaro, John Tran, William J. Dally:
DSD: Regularizing Deep Neural Networks with Dense-Sparse-Dense Training Flow. CoRR abs/1607.04381 (2016) - [i3]Song Han, Junlong Kang, Huizi Mao, Yiming Hu, Xin Li, Yubin Li, Dongliang Xie, Hong Luo, Song Yao, Yu Wang, Huazhong Yang, William J. Dally:
ESE: Efficient Speech Recognition Engine with Compressed LSTM on FPGA. CoRR abs/1612.00694 (2016) - [i2]Chenzhuo Zhu, Song Han, Huizi Mao, William J. Dally:
Trained Ternary Quantization. CoRR abs/1612.01064 (2016) - 2015
- [j1]Milad Mohammadi
, Song Han, Tor M. Aamodt, William J. Dally:
On-Demand Dynamic Branch Prediction. IEEE Comput. Archit. Lett. 14(1): 50-53 (2015) - [c1]Song Han, Jeff Pool, John Tran, William J. Dally:
Learning both Weights and Connections for Efficient Neural Network. NIPS 2015: 1135-1143 - [i1]Song Han, Jeff Pool, John Tran, William J. Dally:
Learning both Weights and Connections for Efficient Neural Networks. CoRR abs/1506.02626 (2015)
Coauthor Index
aka: Fred Chong
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