将标记节点集表示为L,未标记节点设置为U。这项工作的目标是优化半监督图嵌入算法的性能,通过设计一种主动学习查询策略,从U中选择B个节点对数据库进行标签,并添加到L中进行图嵌入训练。 Active Graph Embedding 在给定标记预算的情况下,提出了一种主动图嵌入(AGE)方法来主动选择标记训练实例以优化图嵌入性能。接下来...
This program (AGE) implements an active learning for graph embedding framework, as proposed in the following paper. If you use it for scientific experiments, please cite this paper: @article{DBLP:journals/corr/CaiZC17, author = {HongYun Cai and Vincent Wenchen Zheng and Kevin Chen{-}Chuan Ch...
An Active Noise Correction Graph Embedding Method Based on Active Learning for Graph Noisy DataIn various scenarios of the real world, there are various graph data. Most graph structures are confronted with the problems of complex structure and large consumption of memory space. Graph......
This dataset highlights the impact of active learning. Since dataset is document clustering, preprocessing is the necessary step for achieving the best result. Document representation and word embedding constitute the core of this step. A common approach to represent the document is bag-of-words (N...
Overview Paper Deep Active Learning for Computer Vision: Past and Future Rinyoichi Takezoe1,2, Xu Liu3, Shunan Mao2, Marco Tianyu Chen4, Zhanpeng Feng1, Shiliang Zhang2 and Xiaoyu Wang1∗ 1Intellifusion Inc., China 2Peking University, China 3National University of Singapore, Singapore 4...
d) Stacked bar graph of the number of training annotations is plotted against active-learning iterations (right-most: full annotation count). Bars represent average training samples across 3 seeds. Dashed line indicates the number of samples in the final iteration (77%, n = 81045). e) ...
Active learning in multi-label image classification with graph convolutional network embedding We propose an active learning framework with a GCN embedding and loss prediction module.We propose a dynamic to adjust the AL proportion for more effective... X Xie,M Tian,G Luo,... - 《Future ...
embedding to achieve knowledge point alignment, and based on this, the target knowledge points of learners are located with the help of deep learning; at the same time, the target knowledge points are taken as the starting point to generate the best learning path by traversing the knowledge ...
In this research, we introduced a novel embedding method named as ActiveEm for node embedding in dynamic social networks. The proposed method produces node embeddings based on the activeness of the neighborhood of a node at a given time. Moreover, this method can incorporate node attributes and...
Recently, sparsity preserving projections (SPP) algorithm has been proposed, which combines l 1-graph preserving the sparse reconstructive relationship of ... Z Fei,J Zhang - 《Neurocomputing》 被引量: 65发表: 2011年 Semi-Supervised Representation Learning for Cross-Lingual Text Classification. Cross...