@inproceedings{33e0be18ddc4463c86cea86f1cacc52a,
title = "A new multiple instance algorithm using structural information",
abstract = "Multiple instance learning (MIL) is semisupervised learning that predicts the label of a bag with a wide diversity of instances. It has many applications and thus attracts increasingly more attention. In this paper, we propose a new MIL algorithm using the structural information of a bag to predict its label. In the proposed method, a bag is transformed into a graph, and spectral clustering is employed to divide the graph into several subgraphs. Then, the graph Fourier transform is utilized to extract the features of the subgraphs. Finally, an end-to-end neural network is used to predict the label of a bag with the extracted features. An empirical study with 25 datasets was conducted to validate the effectiveness of the proposed method. The experimental results show that the proposed method performs better than the 6 baseline methods on most datasets.",
keywords = "Multiple instance learning, graph Fourier transform, neural network, spectral cluster",
author = "Xiaoyan Zhu and Ting Wang and Jiayin Wang and Ying Xu and Yuqian Liu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 21st IEEE International Conference on Data Mining, ICDM 2021 ; Conference date: 07-12-2021 Through 10-12-2021",
year = "2021",
doi = "10.1109/ICDM51629.2021.00204",
language = "英语",
series = "Proceedings - IEEE International Conference on Data Mining, ICDM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1553--1558",
editor = "James Bailey and Pauli Miettinen and Koh, \{Yun Sing\} and Dacheng Tao and Xindong Wu",
booktitle = "Proceedings - 21st IEEE International Conference on Data Mining, ICDM 2021",
}