Graph-based machine learningHyperspectral image classificationRemote sensing2022 Elsevier LtdGraph Convolutional Network (GCN) has emerged as a new technique for hyperspectral image (HSI) classification. However, in current GCN-based methods, the graphs are usually constructed with manual effort and thus ...
The iterative cross graph-view sub graph scoring and graph-view weight updating form a closed loop to find optimal sub graphs to represent graphs for multi-graph-view learning. Experiments and comparisons on real-world tasks demonstrate the algorithm's performance. 展开 ...
In this paper, we advance graph classification to handle multi-graph learning for complicated objects, where each object is represented as a bag of graphs and the label is only available to each bag but not individual graphs. In addition, when training classifiers, users are only given a handf...
论文标题:Multi-Level Graph Contrastive Learning论文作者:Pengpeng Shao, Tong Liu, Dawei Zhang, J. Tao, Feihu Che, Guohua Yang论文来源:2021, Neurocomputing论文地址:download论文代码:download 1 Introduction本文贡献:提出多层次图对比学习框架:联合节点级和图级对比学习; 引入KNN 图提取语义信息;...
简单的点击序列建模,可以参考DeepWalk算法(DeepWalk: Online Learning of Social Representations) 使用用户点击过的item,在所有候选item embedding进行近邻搜索,就能够得到与用户点击过的item相似的item,作为召回结果返回。 这个过程通过Faiss计算完成。 2.2 EGES
In this talk, we introduce graph learning as a general approach to model and uncover implicit connections. Based on the emerging unrolling techniques, we consider a graph learning framework that leverages both mathematical designs and end-to-end ...
从负样本的角度来看,论文提出了一种扰动策略,以生成挑战性负样本,以充分探索模态之间的相关性,并确保每个模态在学习表征中的有效贡献。 参考文献:Multi-modal Graph Contrastive Learning for Micro-video Recommendation
Graph-based approaches have been successful in unsupervised and semi-supervised learning. In this paper, we focus on the real-world applications where the same instance can be represented by multiple heterogeneous features. The key point of utilizing the graph-based knowledge to deal with this kind...
我们将这些指标应用于几个知识图基准,以便更好地理解它们的数据结构。此外,我们在这些数据集上评估了我们的模型,实验表明,我们的模型优于最先进的KG推理方法。此外,MPLR能够生成高质量的逻辑规则。 饱和度定义 宏观推理饱和度 我们将宏观推理饱和度定义为查询子图中所涉及到的三元组所占全部三元组的百分比,公式如下:...
We demonstrate the multitask learning capability of the model in the relevant relational problem of estimating network centrality measures, i.e. is vertex v1 more central than vertex v2 given centrality c?. We then show that a GNN can be trained to develop a lingua franca of vertex ...