Results 201 to 210 of about 2,491 (218)

Weight estimation in hypergraph learning

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015
The unremitting rising popularity of social media has led to an exponential increase in web activity as manifested by the vast volume of uploaded images. This boundless volume of image data has triggered the interest in image tagging. Here, an efficient hypergraph weight estimation scheme is proposed that improves the accuracy of image tagging, using ...
Konstantinos Pliakos, Constantine Kotropoulos   +1 more
openaire   +1 more source

Scalable Hypergraph Learning and Processing

2015 IEEE International Conference on Data Mining, 2015
A hypergraph allows a hyperedge to connect more than two vertices, using which to capture the high-order relationships, many hypergraph learning algorithms are shown highly effective in various applications. When learning large hypergraphs, converting them to graphs to employ the distributed graph frameworks is a common approach, yet it results in ...
Jin Huang 0003, Rui Zhang 0003, Jeffrey Xu Yu   +2 more
openaire   +1 more source

Non-adaptive Learning of a Hidden Hypergraph

Theoretical Computer Science, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hasan Abasi, Nader H. Bshouty, Hanna Mazzawi   +2 more
openaire   +2 more sources

Hypergraph Attention Networks for Multimodal Learning

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
One of the fundamental problems that arise in multimodal learning tasks is the disparity of information levels between different modalities. To resolve this problem, we propose Hypergraph Attention Networks (HANs), which define a common semantic space among the modalities with symbolic graphs and extract a joint representation of the modalities based ...
Eun-Sol Kim, Woo-Young Kang, Kyoung-Woon On, Yu-Jung Heo, Byoung-Tak Zhang   +4 more
openaire   +1 more source

Self-supervised hypergraph structure learning

Artificial Intelligence Review
Yanlin Yang, Haixing Zhao, Meng Lei
exaly   +2 more sources

Metric learning based on attribute hypergraph

2017 IEEE International Conference on Image Processing (ICIP), 2017
In this paper, we propose an improved attribute hypergraph learning framework and adapt it for metric learning. Under the attribute hypergraph, each image is abstracted as a vertex and is contained in some hyperedges, each of which represents an attribute.
Yuchun Fang, Yandan Zheng
openaire   +1 more source

Hypergraph regularized sparse feature learning

Neurocomputing, 2017
As an important pre-processing stage in many machine learning and pattern recognition domains, feature selection deems to identify the most discriminate features for a compact data representation. As typical feature selection methods, Lasso and its variants using the l1-norm based regularization have received much attention in recent years.
Mingxia Liu 0001, Jun Zhang 0018, Xiaochun Guo, Liujuan Cao   +3 more
openaire   +1 more source

Self-supervised Hypergraph Representation Learning

2022 IEEE International Conference on Big Data (Big Data), 2022
Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong   +4 more
openaire   +1 more source

Dynamic Hypergraph Learning for Collaborative Filtering

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Chunyu Wei, Jian Liang 0002, Bing Bai, Di Liu 0029   +3 more
openaire   +1 more source

Online Learning for Inexact Hypergraph Search

Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013
Hao Zhang 0010, Liang Huang 0001, Kai Zhao 0003, Ryan T. McDonald   +3 more
openaire   +1 more source