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Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation


Sep 05, 2021
Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen, David Z. Pan

* Accepted by International Conference on Computer Vision (ICCV) 2021 

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DenseLiDAR: A Real-Time Pseudo Dense Depth Guided Depth Completion Network


Aug 28, 2021
Jiaqi Gu, Zhiyu Xiang, Yuwen Ye, Lingxuan Wang

* IEEE Robotics and Automation Letters ( Volume: 6, Issue: 2, April 2021) 
* 9 pages, 7 figures, published in IEEE Robotics and Automation Letters and Accepted by ICRA2021 

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QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits


Aug 02, 2021
Hanrui Wang, Yongshan Ding, Jiaqi Gu, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han

* 14 pages, 22 figures. Code available at https://github.com/mit-han-lab/pytorch-quantum 

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Optimizer Fusion: Efficient Training with Better Locality and Parallelism


Apr 01, 2021
Zixuan Jiang, Jiaqi Gu, Mingjie Liu, Keren Zhu, David Z. Pan

* It is published as a paper at the Hardware Aware Efficient Training (HAET) workshop of ICLR 2021. There are 4 pages excluding references and appendices 

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Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization


Dec 21, 2020
Jiaqi Gu, Chenghao Feng, Zheng Zhao, Zhoufeng Ying, Ray T. Chen, David Z. Pan

* 7 pages content, 2 pages of reference, 6 figures, 4 tables, accepted to Association for the Advancement of Artificial Intelligence (AAAI) 2021 

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Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization


Dec 15, 2020
Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Junior, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. de Abreu, Isac de Souza Campos, Augusto Berndt, Cristina Meinhardt, Jonata T. Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit O. Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee

* In this 23 page manuscript, we explore the connection between machine learning and logic synthesis which was the main goal for International Workshop on logic synthesis. It includes approaches applied by ten teams spanning 6 countries across the world 

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Logic Synthesis Meets Machine Learning:Trading Exactness for Generalization


Dec 04, 2020
Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Junior, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. de Abreu, Isac de Souza Campos, Augusto Berndt, Cristina Meinhardt, Jonata T. Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit O. Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee

* In this 23 page manuscript, we explore the connection between machine learning and logic synthesis which was the main goal for International Workshop on logic synthesis. It includes approaches applied by ten teams spanning 6 countries across the world 

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