Han, Song

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Iandola, F. N., Han, S., Moskewicz, M. W., Ashraf, K., Dally, W. J., & Keutzer, K. (2016) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 6,201

Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Han, S., Mao, H., & Dally, W. J. (2015) · arXiv

Advanced Neural Network ApplicationsAdvanced Data Compression Techniques

Cited by 4,662

EIE: efficient inference engine on compressed deep neural network

Han, S., Liu, X., Mao, H., Pu, J., Pedram, A., Horowitz, M. A., & Dally, W. J. (2016) · ACM SIGARCH Computer Architecture News

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 1,937

Deep Leakage from Gradients

Zhu, L., & Han, S. (2020) · Lecture Notes in Computer Science

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 1,906

Learning both Weights and Connections for Efficient Neural Networks

Han, S., Pool, J., Tran, J., & Dally, W. J. (2015) · arXiv

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 1,481

AMC: AutoML for Model Compression and Acceleration on Mobile Devices

He, Y., Lin, J., Liu, Z., Wang, H., Li, L.-J., & Han, S. (2018) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 1,400

Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation

Liu, Z., Tang, H., Amini, A., Yang, X., Mao, H., Rus, D. L., & Han, S. (2023) · 2023 IEEE International Conference on Robotics and Automation (ICRA)

Autonomous Vehicle Technology and SafetyAdvanced Neural Network Applications

Cited by 1,307

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

Lin, Y., Han, S., Mao, H., Wang, Y., & Dally, W. J. (2017) · arXiv

Stochastic Gradient Optimization TechniquesMachine Learning and Data Classification

Cited by 1,134

EIE: Efficient Inference Engine on Compressed Deep Neural Network

Han, S., Liu, X., Mao, H., Pu, J., Pedram, A., Horowitz, M. A., & Dally, W. J. (2016) · 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA)

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 1,077

Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey

Deng, B. L., Li, G., Han, S., Shi, L., & Xie, Y. (2020) · Proceedings of the IEEE

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 996

HAQ: Hardware-Aware Automated Quantization With Mixed Precision

Wang, K., Liu, Z., Lin, Y., Lin, J., & Han, S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 978

Trained Ternary Quantization

Zhu, C., Han, S., Mao, H., & Dally, W. J. (2016) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 865

Once-for-All: Train One Network and Specialize it for Efficient Deployment

Cai, H., Gan, C., Wang, T., Zhang, Z., & Han, S. (2019) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 845

ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA

Han, S., Kang, J., Mao, H., Hu, Y., Li, X., Li, Y., Xie, D., Luo, H., Yao, S., Wang, Y., et al. (2017) · Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 591

SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning

Wang, H., Zhang, Z., & Han, S. (2021) · 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 427

EfficientViT: Lightweight Multi-Scale Attention for High-Resolution Dense Prediction

Cai, H., Li, J., Hu, M., Gan, C., & Han, S. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 356

AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration

Lin, J., Tang, J., Tang, H., Yang, S., Xiao, G., & Han, S. (2025) · GetMobile: Mobile Computing and Communications

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 274

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Xiao, G., Lin, J., Seznec, M., Wu, H., Demouth, J., & Han, S. (2022) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 247

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

Wang, H., Wu, Z., Liu, Z., Cai, H., Zhu, L., Gan, C., & Han, S. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Advanced Neural Network ApplicationsTopic Modeling

Cited by 227

Exploring the Regularity of Sparse Structure in Convolutional Neural Networks

Mao, H., Han, S., Pool, J., Li, W., Liu, X., Wang, Y., & Dally, W. J. (2017) · arXiv

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 219

GAN Compression: Efficient Architectures for Interactive Conditional GANs

Li, M., Lin, J., Ding, Y., Liu, Z., Zhu, J.-Y., & Han, S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 216

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Lin, J., Tang, J., Tang, H., Yang, S., Chen, W.-M., Wang, W.-C., Xiao, G., Dang, X., Gan, C., & Han, S. (2023) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 103

Software-Hardware Codesign for Efficient Neural Network Acceleration

Guo, K., Han, S., Yao, S., Wang, Y., Xie, Y., & Yang, H. (2017) · IEEE Micro

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 78

Efficient Streaming Language Models with Attention Sinks

Xiao, G., Tian, Y., Chen, B., Han, S., & Lewis, M. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 55