知识蒸馏常见范式(选自https://nervanasystems.github.io/distiller/knowledge_distillation.html) 工作一:Data-Free Learning of Student Networks(arXiv:1904.01186v4) DAFL示意图 本方法涉及一些GAN的知识,可以简单看一下陈诚:通俗理解生成对抗网络GAN。其主要做法是,把训练好的模型(叫做老师模型)作为一种判别器,训练...
Data-free knowledge distillation transfers knowledge by recovering training data from a pre-trained model. Despite the recent success of seeking global dat
To solve these problems, in this paper, we propose a data-free knowledge distillation method called DFPU, which introduce positive-unlabeled (PU) learning. For training a compact neural network without data, a generator is introduced to generate pseudo data under the supervision of the teacher ...
1 前言最近在研究 Data-free KD 和 FL 这块。今天分享一篇CVPR'22的论文: Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning联邦学习(FL)是一种在隐私约束下…
In scenarios like privacy protection or large-scale data transmission, data-free knowledge distillation (DFKD) methods are proposed to learn Knowledge Dist... J Li,S Zhou,L Li,... - 《Neural Networks》 被引量: 0发表: 2024年 Feature Affinity Assisted Knowledge Distillation and Quantization of...
Data-Free Knowledge Distillation For Image Super-Resolution Yiman Zhang1, Hanting Chen1,3, Xinghao Chen1, Yiping Deng2, Chunjing Xu1, Yunhe Wang1* 1 Noah's Ark Lab, Huawei Technologies. 2 Central Software Institution, Huawei Technologies. 3 Key Lab of Machine Perceptio...
Jun 12, 2024 README Apache-2.0 license By He Liu, Yikai Wang, Huaping Liu, Fuchun Sun and Anbang Yao This repository is an official PyTorch implementation of ("Small Scale Data-Free Knowledge Distillation", SSD-KD for short), accepted to CVPR 2024. ...
we propose a data-free knowledge distillation} approach to address heterogeneous FL, where the server learns a lightweight generator to ensemble user information in a data-free manner, which is then broadcasted to users, regulating local training using the learned knowledge as an inductive bias. Em...
data-free knowledge distillation}, author={Tran, Minh-Tuan and Le, Trung and Le, Xuan-May and Harandi, Mehrtash and Tran, Quan Hung and Phung, Dinh}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={23860--23869}, year={2024} } Abou...
Some methods using generative models are also vulnerable to privacy leakage despite their data-free approach due to limitations in defense mechanisms. Online knowledge distillation. The conventional approach involves using a pre-trained teacher model with a larger and more complex architecture to train ...