Multi-view Label EmbeddingMulti-label classificationMulti-view label embeddingLabel space dimension reductionMulti-label classification has been successfully applied to image annotation, information retrieval, text categorization, etc. When the number of classes increases significantly, the traditional multi-...
Multi-view multi-label classification (MvMLC) has garnered significant interest because of its ability to handle complex datasets. However, the inherent complexity of real-world data often results in incomplete views and missing labels, which limit the richness of data and hinder the accurate ...
@inproceedings{liu2023dicnet,title={DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification},author={Liu, Chengliang and Wen, Jie and Luo, Xiaoling and Huang, Chao and Wu, Zhihao and Xu, Yong},booktitle={Proceedings of the AAAI Conference on...
Learning view-specific labels and label-feature dependence maximization for multi-view multi-label classification 2022, Applied Soft Computing Citation Excerpt : In order to handle this problem, scholars have added nonlinear mapping methods to the model. For example, Zhao et al. [34] learns a comm...
Multi-view multi-label (MVML) learning is a framework for solving the problem of associating a single instance with a set of class labels in the presence o
We present GO-LTR, a multi-view multi-label prediction model that relies on a high-order tensor approximation of model weights combined with non-linear activation functions. The model is capable of learning high-order relationships between multiple input views representing the proteins and predicting...
•This paper presents a novel multi-view label embedding algorithm via latent space learning.•The diversity and complementarity are well balanced by HSIC in multi-view learning.•Experiments show that MVLE outperforms the state-of-the-art label embedding methods.论文...
python3 main_multi_view.py -MV_FLAG=CM -MV_TYPE=DAN -MV_TEST_WEIGHT=./weights/DAN.pt # computational efficiency python3 main_multi_view.py -MV_FLAG=COMPUTATION -MV_TYPE=DAN # soft label performance python3 main_single_view.py -SV_FLAG=TEST -SV_TYPE=SAT -SV_TEST_WEIGHT=./weights/...
Multi-label classification refers to learning tasks with each instance belonging to one or more classes simultaneously. It arose from real-world applicatio... X Lin,XW Chen - Acm Conference on Information & Knowledge Management 被引量: 18发表: 2010年 A Unified View of Multi-Label Performance Me...
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。它可以看作是“多视图多标签学习”(Multi-View Multi-Label Learning)遇上了同时属于不完整的多视图和弱标签的数据的一种特殊场景。 就目前来说,这个方向下的研究仍然很...