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Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

Aug 13, 2020
Haotian Tang, Zhijian Liu, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, Song Han

* ECCV 2020. The first two authors contributed equally to this work. Project page: http://spvnas.mit.edu/ 

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Hardware-Centric AutoML for Mixed-Precision Quantization

Aug 11, 2020
Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han

* International Journal of Computer Vision (IJCV), 2020 
* Journal preprint of arXiv:1811.08886 (IJCV, 2020). The first three authors contributed equally to this work. Project page: https://hanlab.mit.edu/projects/haq/ 

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Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning

Jul 28, 2020
Han Cai, Chuang Gan, Ligeng Zhu, Song Han


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MCUNet: Tiny Deep Learning on IoT Devices

Jul 20, 2020
Ji Lin, Wei-Ming Chen, Yujun Lin, John Cohn, Chuang Gan, Song Han

* Demo video available here: https://youtu.be/YvioBgtec4U 

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Differentiable Augmentation for Data-Efficient GAN Training

Jun 18, 2020
Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han


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APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

Jun 15, 2020
Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Song Han

* Accepted by CVPR 2020 

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HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

May 28, 2020
Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han

* Accepted to ACL 2020. 14 pages, 12 figures. Code available at http://github.com/mit-han-lab/hardware-aware-transformers.git 

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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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