To mitigate such problems, we propose a simple but effective unsupervised domain adaptation method, adversarial adaptation with distillation (AAD), which combines the adversarial discriminative domain adaptation (ADDA) framework with knowledge distillation. We evaluate our approach in the task of cross-...
Data-Free Network Quantization With Adversarial Knowledge Distillation 1. Introduction 在本文中,我们提出了一个对抗性知识提炼框架,在无法获得原始训练数据的损失时,通过对抗性学习使最坏情况下的可能损失(最大损失)最小化。与[36]的关键区别在于,给定任何元数据,我们利用它们来约束对抗性学习框架中的发生器。为了...
Learning from Noisy Labels with Distillation. Li, Yuncheng et al. ICCV 2017 Training Deep Neural Networks in Generations:A More Tolerant Teacher Educates Better Students. arXiv:1805.05551 Knowledge distillation by on-the-fly native ensemble. Lan, Xu et al. NIPS 2018 Learning Metrics from Teachers...
(2017). Domain adaptation of dnn acoustic models using knowledge distillation. In ICASSP. Ashok, A., Rhinehart, N., Beainy, F., & Kitani, K. M. (2018). N2N learning: Network to network compression via policy gradient reinforcement learning. In ICLR. Asif, U., Tang, J. & Harrer, S...
domain is evolving, e.g. spam detection where attackers continuously change their tactics. To fill this gap, we propose Knowledge Adaptation, an extension of Knowledge Distillation (Bucilua et al., 2006; Hinton et al., 2015) to the domain adaptation scenario. We show how a student model ...
Learning from Noisy Labels with Distillation. Li, Yuncheng et al. ICCV 2017 Training Deep Neural Networks in Generations:A More Tolerant Teacher Educates Better Students. arXiv:1805.05551 Knowledge distillation by on-the-fly native ensemble. Lan, Xu et al. NIPS 2018 ...
1 code implementation•7 Jul 2021 With the contribution of the CCD and CRP, our CRCKD algorithm can distill the relational knowledge more comprehensively. Image ClassificationKnowledge Distillation+2 18 Paper Code
Knowledge Distillation via the Target-aware Transformer Sihao Lin1,3†‡, Hongwei Xie2†, Bing Wang2, Kaicheng Yu2, Xiaojun Chang3§, Xiaodan Liang4, Gang Wang2 1RMIT University 2Alibaba Group 3ReLER, AAII, UTS 4Sun Yat-sen University {linsihao6, hongwei.xie.90, Kaich...
For example, distillation methods have been successfully used to tackle domain adaptation tasks [47–49]. In this chapter, we presented the most important tools that DL practitioners and researchers can employ to this end. That is, we presented the neural network distillation approach, which can ...
Multi-source Distilling Domain Adaptation. Zhao, Sicheng et al. arXiv:1911.11554 Application of KD Face model compression by distilling knowledge from neurons. Luo, Ping et al. AAAI 2016 Learning efficient object detection models with knowledge distillation. Chen, Guobin et al. NIPS 2017 ...