Rongyao Hu

According to our database, Rongyao Hu authored at least 40 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Hierarchical graph learning with convolutional network for brain disease prediction.

Tong Liu, Fangqi Liu, Yingying Wan, Rongyao Hu, Yongxin Zhu, Li Li

Multim. Tools Appl., May, 2024

Reverse Graph Learning for Graph Neural Network.

Liang Peng, Rongyao Hu, Fei Kong, Jiangzhang Gan, Yujie Mo, Xiaoshuang Shi, Xiaofeng Zhu

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Multigraph Fusion for Dynamic Graph Convolutional Network.

Jiangzhang Gan, Rongyao Hu, Yujie Mo, Zhao Kang, Liang Peng, Yonghua Zhu, Xiaofeng Zhu

IEEE Trans. Neural Networks Learn. Syst., January, 2024

Towards Dynamic-Prompting Collaboration for Source-Free Domain Adaptation.

Mengmeng Zhan, Zongqian Wu, Rongyao Hu, Ping Hu, Heng Tao Shen, Xiaofeng Zhu

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

GATrack: Group-Aware features for multiple object tracking.

Xiaolong Wang, Ping Hu, Rongyao Hu, Xiaofeng Zhu

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Unsupervised Anomaly Detection for Multivariate Time Series Using Diffusion Model.

Rongyao Hu, Xinyu Yuan, Yan Qiao, Benchu Zhang, Pei Zhao

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

IGCNN-FC: Boosting interpretability and generalization of convolutional neural networks for few chest X-rays analysis.

Mengmeng Zhan, Xiaoshuang Shi, Fangqi Liu, Rongyao Hu

Inf. Process. Manag., May, 2023

Completed sample correlations and feature dependency-based unsupervised feature selection.

Tong Liu, Rongyao Hu, Yongxin Zhu

Multim. Tools Appl., April, 2023

Traffic Matrix Estimation based on Denoising Diffusion Probabilistic Model.

Xinyu Yuan, Yan Qiao, Pei Zhao, Rongyao Hu, Benchu Zhang

Proceedings of the IEEE Symposium on Computers and Communications, 2023

2022

Multi-task multi-modality SVM for early COVID-19 Diagnosis using chest CT data.

Rongyao Hu, Jiangzhang Gan, Xiaofeng Zhu, Tong Liu, Xiaoshuang Shi

Inf. Process. Manag., 2022

Complementary Graph Representation Learning for Functional Neuroimaging Identification.

Rongyao Hu, Liang Peng, Jiangzhang Gan, Xiaoshuang Shi, Xiaofeng Zhu

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Multi-view Unsupervised Graph Representation Learning.

Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Multi-Band Brain Network Analysis for Functional Neuroimaging Biomarker Identification.

Rongyao Hu, Zi-Wen Peng, Xiaofeng Zhu, Jiangzhang Gan, Yonghua Zhu, Junbo Ma, Guorong Wu

IEEE Trans. Medical Imaging, 2021

Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan.

Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen

Medical Image Anal., 2021

Brain functional connectivity analysis based on multi-graph fusion.

Jiangzhang Gan, Zi-Wen Peng, Xiaofeng Zhu, Rongyao Hu, Junbo Ma, Guorong Wu

Medical Image Anal., 2021

Adaptive reverse graph learning for robust subspace learning.

Chang-An Yuan, Zhi Zhong, Cong Lei, Xiaofeng Zhu, Rongyao Hu

Inf. Process. Manag., 2021

Adaptive Laplacian Support Vector Machine for Semi-supervised Learning.

Rongyao Hu, Leyuan Zhang, Jian Wei

Comput. J., 2021

Multi-scale Graph Fusion for Co-saliency Detection.

Rongyao Hu, Zhenyun Deng, Xiaofeng Zhu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Robust SVM with adaptive graph learning.

Rongyao Hu, Xiaofeng Zhu, Yonghua Zhu, Jiangzhang Gan

World Wide Web, 2020

Multi-graph Fusion for Functional Neuroimaging Biomarker Detection.

Jiangzhang Gan, Xiaofeng Zhu, Rongyao Hu, Yonghua Zhu, Junbo Ma, Zi-Wen Peng, Guorong Wu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Low-rank hypergraph feature selection for multi-output regression.

Xiaofeng Zhu, Rongyao Hu, Cong Lei, Kim-Han Thung, Wei Zheng, Can Wang

World Wide Web, 2019

One-Step Multi-View Spectral Clustering.

Xiaofeng Zhu, Shichao Zhang, Wei He, Rongyao Hu, Cong Lei, Pengfei Zhu

IEEE Trans. Knowl. Data Eng., 2019

2018

Supervised feature selection algorithm via discriminative ridge regression.

Shichao Zhang, Debo Cheng, Rongyao Hu, Zhenyun Deng

World Wide Web, 2018

Local and Global Structure Preservation for Robust Unsupervised Spectral Feature Selection.

Xiaofeng Zhu, Shichao Zhang, Rongyao Hu, Yonghua Zhu, Jingkuan Song

IEEE Trans. Knowl. Data Eng., 2018

Adaptive structure learning for low-rank supervised feature selection.

Yonghua Zhu, Xuejun Zhang, Rongyao Hu, Guoqiu Wen

Pattern Recognit. Lett., 2018

Unsupervised feature selection by combining subspace learning with feature self-representation.

Yangding Li, Cong Lei, Yue Fang, Rongyao Hu, Yonggang Li, Shichao Zhang

Pattern Recognit. Lett., 2018

Dynamic graph learning for spectral feature selection.

Wei Zheng, Xiaofeng Zhu, Yonghua Zhu, Rongyao Hu, Cong Lei

Multim. Tools Appl., 2018

2017

Low-rank feature selection for multi-view regression.

Rongyao Hu, Debo Cheng, Wei He, Guoqiu Wen, Yonghua Zhu, Jilian Zhang, Shichao Zhang

Multim. Tools Appl., 2017

Low-rank unsupervised graph feature selection via feature self-representation.

Wei He, Xiaofeng Zhu, Debo Cheng, Rongyao Hu, Shichao Zhang

Multim. Tools Appl., 2017

Graph self-representation method for unsupervised feature selection.

Rongyao Hu, Xiaofeng Zhu, Debo Cheng, Wei He, Yan Yan, Jingkuan Song, Shichao Zhang

Neurocomputing, 2017

Self-representation dimensionality reduction for multi-model classification.

Rongyao Hu, Jie Cao, Debo Cheng, Wei He, Yonghua Zhu, Qing Xie, Guoqiu Wen

Neurocomputing, 2017

Unsupervised feature selection for visual classification via feature-representation property.

Wei He, Xiaofeng Zhu, Debo Cheng, Rongyao Hu, Shichao Zhang

Neurocomputing, 2017

Feature self-representation based hypergraph unsupervised feature selection via low-rank representation.

Wei He, Xiaohui Cheng, Rongyao Hu, Yonghua Zhu, Guoqiu Wen

Neurocomputing, 2017

Adaptive Hypergraph Learning for Unsupervised Feature Selection.

Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang, Rongyao Hu, Wei He

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Robust Features Selection via Structure Learning and Multiple Subspace Learning.

Yonghua Zhu, Xuejun Zhang, Rongyao Hu, Guoqiu Wen

Proceedings of the IEEE International Conference on Big Knowledge, 2017

Unsupervised Spectral Feature Selection with Local Structure Learning.

Shichao Zhang, Yue Fang, Cong Lei, Yangding Li, Rongyao Hu, Yonggang Li

Proceedings of the IEEE International Conference on Big Knowledge, 2017

Unsupervised Feature Selection via Local Structure Learning and Self-Representation.

Shichao Zhang, Cong Lei, Yue Fang, Yangding Li, Rongyao Hu, Xiaoyi Hu

Proceedings of the IEEE International Conference on Big Knowledge, 2017

One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace.

Xiaofeng Zhu, Wei He, Yonggang Li, Yang Yang, Shichao Zhang, Rongyao Hu, Yonghua Zhu

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Supervised Feature Selection by Robust Sparse Reduced-Rank Regression.

Rongyao Hu, Xiaofeng Zhu, Wei He, Jilian Zhang, Shichao Zhang

Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016

Unsupervised Hypergraph Feature Selection with Low-Rank and Self-Representation Constraints.

Wei He, Xiaofeng Zhu, Yonggang Li, Rongyao Hu, Yonghua Zhu, Shichao Zhang

Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016