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We address the challenge of producing trustworthy and accurate compact models for edge devices.
Model compression
Cristian Buciluǎ, Rich Caruana, and Alexandru Niculescu-Mizil · 2006
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Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Fitnets: Hints for thin deep nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean, et al · 2015
Earlier work this paper cites.
Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 2015
Earlier work this paper cites.
Sergey Zagoruyko and Nikos Komodakis · 2016
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
Earlier work this paper cites.
Learning from noisy labels with distillation
Yuncheng Li, Jianchao Yang, Yale Song, Liangliang Cao, Jiebo Luo, and Li-Jia Li · 2017
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Deep mutual learning
Ying Zhang, Tao Xiang, Timothy M Hospedales, and Huchuan Lu · 2018
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Online knowledge distillation with diverse peers
Defang Chen, Jian-Ping Mei, Can Wang, Yan Feng, and Chun Chen · 2019
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Knowledge distillation via route constrained optimization
Xiao Jin, Baoyun Peng, Yichao Wu, Yu Liu, Jiaheng Liu, Ding Liang, Junjie Yan, and Xiaolin Hu · 2019
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Relational knowledge distillation
Wonpyo Park, Dongju Kim, Yan Lu, and Minsu Cho · 2019
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Online knowledge distillation via collaborative learning
Qiushan Guo, Xinjiang Wang, Yichao Wu, Zhipeng Yu, Ding Liang, Xiaolin Hu, and Ping Luo · 2020
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Improved knowledge distillation via teacher assistant
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, and Hassan Ghasemzadeh · 2020
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A statistical perspective on distillation
Aditya K Menon, Ankit Singh Rawat, Sashank Reddi, Seungyeon Kim, and Sanjiv Kumar · 2021
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Does knowledge distillation really work?
Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A Alemi, and Andrew G Wilson · 2021
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Switchable online knowledge distillation
Biao Qian, Yang Wang, Hongzhi Yin, Richang Hong, and Meng Wang · 2022
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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Similarity-preserving knowledge distillation
Frederick Tung and Greg Mori · 2019
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Symmetric cross entropy for robust learning with noisy labels
Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, and James Bailey · 2019
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Feature-map-level online adversarial knowledge distillation
Inseop Chung, SeongUk Park, Jangho Kim, and Nojun Kwak · 2020
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Biao Qian, Yang Wang, Hongzhi Yin, Richang Hong, and Meng Wang · 2022
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Robust distillation for worst-class performance
Serena Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, and Aditya Krishna Menon · 2022
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Decoupled knowledge distillation
Borui Zhao, Quan Cui, Renjie Song, Yiyu Qiu, and Jiajun Liang · 2022
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