Explaining Knowledge Distillation by Quantifying the Knowledge

Explaining Knowledge Distillation by Quantifying the Knowledge

Computer Vision and Pattern Recognition (CVPR), 2025

7 March 2020

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Papers citing "Explaining Knowledge Distillation by Quantifying the Knowledge"

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Title
Hands-on Guidance for Distilling Object Detectors Yangyang Qin H. Ling Zhenghai He Yuxuan Shi Lei Wu ObjD FedML 64 1 0 26 Mar 2021
Joint framework with deep feature distillation and adaptive focal loss for weakly supervised audio tagging and acoustic event detection Yunhao Liang Yanhua Long Yijie Li Jiaen Liang Yuping Wang 87 10 0 23 Mar 2021
Student Network Learning via Evolutionary Knowledge Distillation Kangkai Zhang Chunhui Zhang Shikun Li Dan Zeng Shiming Ge 103 93 0 23 Mar 2021
Spectral Roll-off Points Variations: Exploring Useful Information in Feature Maps by Its Variations Yunkai Yu Yuyang You Zhihong Yang Guozheng Liu Peiyao Li Zhicheng Yang Wenjing Shan 91 2 0 31 Jan 2021
Multi-level Knowledge Distillation via Knowledge Alignment and Correlation Fei Ding Yin Yang Hongxin Hu Venkat Krovi Feng Luo 67 4 0 01 Dec 2020
A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions Rahul Mishra Hari Prabhat Gupta Tanima Dutta 92 96 0 05 Oct 2020
Differential Replication in Machine Learning Irene Unceta Jordi Nin O. Pujol SyDa 61 1 0 15 Jul 2020
On the Demystification of Knowledge Distillation: A Residual Network Perspective N. Jha Rajat Saini Sparsh Mittal 78 4 0 30 Jun 2020
Interpreting and Disentangling Feature Components of Various Complexity from DNNs Jie Ren Mingjie Li Zexu Liu Quanshi Zhang CoGe 138 20 0 29 Jun 2020
Knowledge Distillation: A Survey Jianping Gou B. Yu Stephen J. Maybank Dacheng Tao VLM 694 3,365 0 09 Jun 2020