这种情况下,使用PTQ(训练后量化)是一种策略,还有一些策略也可以近似完成该任务,比如:无数据蒸馏。 Data-Free Knowledge Distillation for Deep Neural Networks 文章模型压缩pipeline:在所有数据上训好的teacher模型及部分数据metadata --> 使用metadata和模型重建数据集--&...
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...
其中，Dream Distillation提出了一个颇具吸引力的方案，它利用10%的真实数据和聚类生成的数据对WRN模型进行了优化，尽管效果显著，但对数据的需求仍然较大。而Data-Free Learning则尝试利用生成对抗网络(GAN)生成数据，不过它仍然受限于对真实数据的依赖。为了更直接地逼近真实数据的特性，一种新的数据生成方...
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping O网页链接ChatPaper综述:该论文介绍了一种新型技术,称为BOOT,可以通过有效的数据无关的蒸馏算法来解决扩散模型性能下降的问题。原因是由于迭代去噪导致生成速度缓慢。传统蒸馏方法需要实时数据或离线合成大量的训练数据,而BOOT则不需要这些...
Large-Scale Generative Data-Free Distillation 星级: 12 页 DaST: Data-free Substitute Training for Adversarial Attacks 星级: 10 页 Data-Free Network Quantization With Adversarial Knowledge Distillation 星级: 11 页 Data-Free and Data-Driven RANS Predictions with Quantified Uncertainty 星级: 24 ...
Zero-shot knowledge distillationRegressionKnowledge distillation has been used successfully to compress a large neural network (teacher) into a smaller neural network (student) by transferring the knowledge of the teacher network with its original training dataset. However, the original training dataset ...
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...
Data-free Knowledge Distillation for Object Detection We present DeepInversion for Object Detection (DIODE) to enable data-free knowledge distillation for neural networks trained on the object detection task. ... A Chawla,H Yin,P Molchanov,... - Workshop on Applications of Computer Vision 被引量...
Paper tables with annotated results for Data-Free Distillation of Language Model by Text-to-Text Transfer
or on a dataset whose release posesprivacy or safety concerns as may be the casefor biometrics tasks. We present a method fordata-free knowledge distillation, which is ableto compress deep neural networks trained onlarge-scale datasets to a fraction of their sizeleveraging only some extra metadat...