Song Han

University of Connecticut

MicroNet for Efficient Language Modeling

May 16, 2020
Zhongxia Yan, Hanrui Wang, Demi Guo, Song Han

* Accepted by PMLR 
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GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning

Apr 30, 2020
Hanrui Wang, Kuan Wang, Jiacheng Yang, Linxiao Shen, Nan Sun, Hae-Seung Lee, Song Han

* Accepted to the 57th Design Automation Conference (DAC 2020); 6 pages, 8 figures 
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Lite Transformer with Long-Short Range Attention

Apr 24, 2020
Zhanghao Wu, Zhijian Liu, Ji Lin, Yujun Lin, Song Han

* ICLR 2020. The first two authors contributed equally to this work 
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GAN Compression: Efficient Architectures for Interactive Conditional GANs

Mar 19, 2020
Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han


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Training Kinetics in 15 Minutes: Large-scale Distributed Training on Videos

Oct 01, 2019
Ji Lin, Chuang Gan, Song Han


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

Aug 26, 2019
Han Cai, Chuang Gan, Song Han


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Point-Voxel CNN for Efficient 3D Deep Learning

Jul 08, 2019
Zhijian Liu, Haotian Tang, Yujun Lin, Song Han

* The first two authors contributed equally to this work 
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Deep Leakage from Gradients

Jun 21, 2019
Ligeng Zhu, Zhijian Liu, Song Han


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SysML: The New Frontier of Machine Learning Systems

May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros 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 Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar


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Design Automation for Efficient Deep Learning Computing

Apr 24, 2019
Song Han, Han Cai, Ligeng Zhu, Ji Lin, Kuan Wang, Zhijian Liu, Yujun Lin


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Defensive Quantization: When Efficiency Meets Robustness

Apr 17, 2019
Ji Lin, Chuang Gan, Song Han


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Learning to Design Circuits

Jan 17, 2019
Hanrui Wang, Jiacheng Yang, Hae-Seung Lee, Song Han

* The first two authors contributed equally to this work 
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HAQ: Hardware-Aware Automated Quantization

Dec 06, 2018
Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han

* The first three authors contributed equally to this work. Project page: https://hanlab.mit.edu/projects/haq/ 
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ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

Dec 02, 2018
Han Cai, Ligeng Zhu, Song Han

* Submitted to ICLR 2019 
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Temporal Shift Module for Efficient Video Understanding

Nov 20, 2018
Ji Lin, Chuang Gan, Song Han

* Our framework ranks the first on both Something-Something V1 and V2 leaderboards upon this paper's submission. Measured on P100 GPU, our single model achieved 1.8% higher accuracy at 8x lower latency and 12x higher throughput compared to I3D 
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AMC: AutoML for Model Compression and Acceleration on Mobile Devices

Aug 26, 2018
Yihui He, Ji Lin, Zhijian Liu, Hanrui Wang, Li-Jia Li, Song Han


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Fast inference of deep neural networks in FPGAs for particle physics

Jun 28, 2018
Javier Duarte, Song Han, Philip Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Jennifer Ngadiuba, Maurizio Pierini, Ryan Rivera, Nhan Tran, Zhenbin Wu

* 22 pages, 17 figures, 2 tables, JINST revision 
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Path-Level Network Transformation for Efficient Architecture Search

Jun 07, 2018
Han Cai, Jiacheng Yang, Weinan Zhang, Song Han, Yong Yu

* ICML 2018 
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Efficient Sparse-Winograd Convolutional Neural Networks

Feb 18, 2018
Xingyu Liu, Jeff Pool, Song Han, William J. Dally

* Published as a conference paper at ICLR 2018 
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Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

Feb 05, 2018
Yujun Lin, Song Han, Huizi Mao, Yu Wang, William J. Dally

* ICLR 2018 
 * we find 99.9% of the gradient exchange in distributed SGD is redundant; we reduce the communication bandwidth by two orders of magnitude without losing accuracy 
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Exploring the Regularity of Sparse Structure in Convolutional Neural Networks

Jun 05, 2017
Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J. Dally

* submitted to NIPS 2017 
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Deep Generative Adversarial Networks for Compressed Sensing Automates MRI

May 31, 2017
Morteza Mardani, Enhao Gong, Joseph Y. Cheng, Shreyas Vasanawala, Greg Zaharchuk, Marcus Alley, Neil Thakur, Song Han, William Dally, John M. Pauly, Lei Xing


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Trained Ternary Quantization

Feb 23, 2017
Chenzhuo Zhu, Song Han, Huizi Mao, William J. Dally

* Accepted for Poster Presentation on ICLR 2017 
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DSD: Dense-Sparse-Dense Training for Deep Neural Networks

Feb 21, 2017
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

* Published as a conference paper at ICLR 2017 
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ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA

Feb 20, 2017
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

* Accepted as full paper in FPGA'17, Monterey, CA; Also appeared at 1st International Workshop on Efficient Methods for Deep Neural Networks at NIPS 2016, Barcelona, Spain 
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Classification of Neurological Gait Disorders Using Multi-task Feature Learning

Feb 01, 2017
Ioannis Papavasileiou, Wenlong Zhang, Xin Wang, Jinbo Bi, Li Zhang, Song Han

* shorter version of this paper is submitted to CHASE '17 conference 
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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Nov 04, 2016
Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, Kurt Keutzer

* In ICLR Format 
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EIE: Efficient Inference Engine on Compressed Deep Neural Network

May 03, 2016
Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark A. Horowitz, William J. Dally

* External Links: TheNextPlatform: http://goo.gl/f7qX0L ; O'Reilly: https://goo.gl/Id1HNT ; Hacker News: https://goo.gl/KM72SV ; Embedded-vision: http://goo.gl/joQNg8 ; Talk at NVIDIA GTC'16: http://goo.gl/6wJYvn ; Talk at Embedded Vision Summit: https://goo.gl/7abFNe ; Talk at Stanford University: https://goo.gl/6lwuer. Published as a conference paper in ISCA 2016 
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