Rongyao Hu

According to our database1, Rongyao Hu authored at least 36 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Reverse Graph Learning for Graph Neural Network.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

Multigraph Fusion for Dynamic Graph Convolutional Network.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

2023
IGCNN-FC: Boosting interpretability and generalization of convolutional neural networks for few chest X-rays analysis.
Inf. Process. Manag., May, 2023

Completed sample correlations and feature dependency-based unsupervised feature selection.
Multim. Tools Appl., April, 2023

Traffic Matrix Estimation based on Denoising Diffusion Probabilistic Model.
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.
Inf. Process. Manag., 2022

Complementary Graph Representation Learning for Functional Neuroimaging Identification.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Multi-view Unsupervised Graph Representation Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
Multi-Band Brain Network Analysis for Functional Neuroimaging Biomarker Identification.
IEEE Trans. Medical Imaging, 2021

Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan.
Medical Image Anal., 2021

Brain functional connectivity analysis based on multi-graph fusion.
Medical Image Anal., 2021

Adaptive reverse graph learning for robust subspace learning.
Inf. Process. Manag., 2021

Adaptive Laplacian Support Vector Machine for Semi-supervised Learning.
Comput. J., 2021

Multi-scale Graph Fusion for Co-saliency Detection.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Robust SVM with adaptive graph learning.
World Wide Web, 2020

Multi-graph Fusion for Functional Neuroimaging Biomarker Detection.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Low-rank hypergraph feature selection for multi-output regression.
World Wide Web, 2019

One-Step Multi-View Spectral Clustering.
IEEE Trans. Knowl. Data Eng., 2019

2018
Supervised feature selection algorithm via discriminative ridge regression.
World Wide Web, 2018

Local and Global Structure Preservation for Robust Unsupervised Spectral Feature Selection.
IEEE Trans. Knowl. Data Eng., 2018

Adaptive structure learning for low-rank supervised feature selection.
Pattern Recognit. Lett., 2018

Unsupervised feature selection by combining subspace learning with feature self-representation.
Pattern Recognit. Lett., 2018

Dynamic graph learning for spectral feature selection.
Multim. Tools Appl., 2018

2017
Low-rank feature selection for multi-view regression.
Multim. Tools Appl., 2017

Low-rank unsupervised graph feature selection via feature self-representation.
Multim. Tools Appl., 2017

Graph self-representation method for unsupervised feature selection.
Neurocomputing, 2017

Self-representation dimensionality reduction for multi-model classification.
Neurocomputing, 2017

Unsupervised feature selection for visual classification via feature-representation property.
Neurocomputing, 2017

Feature self-representation based hypergraph unsupervised feature selection via low-rank representation.
Neurocomputing, 2017

Adaptive Hypergraph Learning for Unsupervised Feature Selection.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Robust Features Selection via Structure Learning and Multiple Subspace Learning.
Proceedings of the IEEE International Conference on Big Knowledge, 2017

Unsupervised Spectral Feature Selection with Local Structure Learning.
Proceedings of the IEEE International Conference on Big Knowledge, 2017

Unsupervised Feature Selection via Local Structure Learning and Self-Representation.
Proceedings of the IEEE International Conference on Big Knowledge, 2017

One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Supervised Feature Selection by Robust Sparse Reduced-Rank Regression.
Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016

Unsupervised Hypergraph Feature Selection with Low-Rank and Self-Representation Constraints.
Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016


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