Graph Self-Supervised Learning: A Surveyieeexplore.ieee.org/abstract/document/9770382 PDF: https://arxiv.org/pdf/2103.00111.pdfarxiv.org/pdf/2103.00111.pdf 1. 背景与概括 图的深度学习作为一个热门领域引起了广泛的研究兴趣,但是由于当前研究大多集中在半监督或者监督学习上,存在标签依赖严重、泛...
而比较恼人的是,这个predictive learning和contrastive learning的区分问题。 从下文对于predict learning的定义中可以看到: “如果模型能够从其他被掩盖或损坏的特征中推断出原始特征,则预计该模型在下游任务中是有效的”,predictive learning更接近于survey中提到的以autoencoder为代表的生成式自监督模型,因此下面中,将pred...
【图深度自监督学习Philips S. Yu团队重磅新作】Graph Self-Supervised Learning: A Survey,程序员大本营,技术文章内容聚合第一站。
论文标题:Self-supervised Learning on Graphs: Contrastive, Generative,or Predictive论文作者:Lirong Wu, Haitao Lin, Cheng Tan,Zhangyang Gao, and Stan.Z.Li论文来源:2022, ArXiv论文地址:download 1介绍图深度学习的发展是由于能够捕获图的结构和节点/边特征。
A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends Jie Gui, Senior Member, IEEE, Tuo Chen, Jing 自监督学习,在google scholar上检索,在2021年一年就产生了18,900 相关文章,也就是每天大概52篇相关工作发表出来。文章数量也是逐年上升,尤其是你可以去各大任务的SOTA工作看一下...
Graph Self-Supervised Learning: A Survey 作者:Philip S. Yu等 主要工作: 对图自监督学习进行归类 总结了已有的图自监督学习的工作 提出了对后续的图自监督学习工作方向的展望 相较于已有的图自监督学习综述,他们的工作对这块分得更科学更细致 Introduction 部分 ...
Keywords: contrastive learning; self-supervised learning; discriminative(有区别的) learning; image/video classification; object detection; unsupervised learning; transfer learning 翻译:自监督学习因为它可以避免给大规模数据做标注的成本而获得普及。它有能力采用自定义的伪标签做监督并使用学习好的模型表示几个下游...
Among all the learning paradigms, Self-Supervised Learning (SSL), an unsupervised training paradigm that mines effective information from the data itself, is considered as an essential solution to solve the time-consuming and labor-intensive data labeling problems via smart pre-training task design. ...
【Arxiv-2021】【IEEE members/fellows】Graph Self-Supervised Learning: A Survey 核心要点 文章旨在对现有图神经网络的方法进行全面的总结和分类,并给出常用的数据集、评估基准、方法间的性能比较和开源代码链接。图的深度学习的热度与日俱增,但大多数工作集中在(半)监督学习上。对比标签的严重依赖导致模型泛化能力...
Although supervised learning has been highly successful in improving the state-of-the-art in the domain of image-based computer vision in the past, the margin of improvement has diminished significantly in recent years, indicating that a plateau is in sight. Meanwhile, the use of self-supervised...