Extensive experiments on three weakly labeled learning tasks, namely, (i) semi-supervised multi-label learning; (ii) weak label learning and (iii) extended weak label learning, clearly show that our proposal improves the safeness of using weakly labeled data compared with many state-of-the-art ...
Weak-label: multi-Label Learning With Missing Labels. Partial Multi-label: In practice, the complicated structure of the label space usually makes it hard to decide some hard labels are relevant or not. Partial multi-label preserves all the potentially correct labels. The remaining labels are cal...
（3）WELL(Multi-Label Learning with Weak Label)：http://ai2-s2-pdfs.s3.amazonaws.com/4642/9...
近年来有许多基于“相似的实例具有相似的标签“假设的“弱标签学习”(Weak-Label Learning)方法[5-8]被提出来解决这种数据造成的预测效果下降。 不完整的多视图弱标签学习 显而易见,“不完整的多视图弱标签学习”(Incomplete Multi-View Weak-Label Learning)是“不完整的多视图学习”与“弱标签学习”的交叉子方向。
Multi-label learning with weak label. AAAI, 2010. [52] Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna. Rethinking the inception ar- chitecture for computer vision. CVPR, 2016. [53] Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Al...
2. 多类VS多标签 3. 加载和生成多标签数据集 4. 解决多标签分类的方法 问题转换法 自适应算法 集成...
论文笔记(二):Multi-Label Balancing with Selective Learning for Attribute Prediction,程序员大本营,技术文章内容聚合第一站。
For this application, we tackle an open challenge with training CNNs - identifying weak scattered patterns with diffuse background interference, which is common in scientific imaging. We articulate an Attentional Aggregation Module (AAM) to enhance feature representations. First, we reweight and high...
Multi-label learning originated from the investigation of text categorization problem, where each document may belong to several predefined topics simultaneously. In multi-label learning, the training set is composed of instances each associated with a set of labels, and the task is to predict the ...
Multi-label learning with weak label AAAI, 2010 Multi-label learning with incomplete class assignments CVPR, 2011 Fast image tagging ICML, 2013 Revisiting unreasonable effectiveness of data in deep learning era ICCV, 2017 Binary codes embedding for fast image tagging with incomplete labels ECCV, 2014...