论文标题:Data Augmentation for Deep Graph Learning: A Survey 论文作者:Kaize Ding, Zhe Xu, Hanghang Tong, Huan Liu 论文来源:2022, arXiv 论文地址:download 1 介绍 本文主要总结图数据增强,并对该领域的代表性方法做出归类分析。 DGL 存在的两个问题: ...
我们进一步将图数据增强的应用总结进两个代表性的data-centric的深度图学习的问题:(1)reliable graph learning:关注增强输入图的效用以及模型容量(通过图数据增强)(2)low-resource graph learning:目标是通过数据增强来增强带标签的训练数据范围。 1. introduction 本文的贡献如下: (1)本文是GraphDA(图数据增强)的第...
Data Augmentation beyond Simple Graphs Data Augmentation for Graph Imbalanced Training Learnable and Generalizable Graph Augmentation 参考 ^Songtao Liu, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, and Dinghao Wu. Local augmentation for graph neural networks. arXiv prep...
[LG] A Survey on Data Augmentation in Large Model Era http://t.cn/A6jFcRbY 关于大型模型数据增强方法的综述。大型模型在语言和扩散模型方面显示出了卓越的性能,但是训练这些大型模型需要大量高质量的数...
C. Shorten and T. M. Khoshgoftaar, ‘A survey on Image Data Augmentation for Deep Learning’, J Big Data, vol. 6, no. 1, p. 60, Dec. 2019, doi: 10.1186/
survey focuses on Data Augmentation, a data-space solution to the problem of limited data. Data Augmentation encompasses a suite of techniques that enhance the size and quality of training datasets such that better Deep Learning models can be built using them. The image augmentation algorithms ...
Felina 计算机科学等 4 个话题下的优秀答主 A Survey on Data Synthesis and Augmentation for Large Language ModelsLink:链接 发布于 2024-10-27 04:08・IP 属地浙江 赞同5 分享收藏 写下你的评论... 1 条评论 默认 最新 小盘同学 2024-10-27· 广东 回复喜欢...
This survey focuses on Data Augmentation, a data-space solution to the problem of limited data. Data Augmentation encompasses a suite of techniques that enhance the size and quality of training datasets such that better Deep Learning models can be built using them. The image augmentation algorithms...
As an effective way to enhance the size and quality of the training data, data augmentation is crucial to the successful application of deep learning models on time series data. In this paper, we systematically review different data augmentation methods for time series. We propose a taxonomy for...
Data augmentationSpeech recognitionData augmentation has been proposed as a method to increase the quantity of training data. It is a common strategy adopted to avoid over-fitting, reduce mismatch and improve robustness of the models. But, would the system performance improve if we add data of ...