Yu Wang

Orcid: 0000-0002-4788-8655

Affiliations:

Tianjin University, School of Artificial Intelligence, Tianjin, China
Tianjin University, School of Computer Science and Technology, Tianjin, China

According to our database¹, Yu Wang authored at least 38 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2024

Multiview Tensor Spectral Clustering via Co-Regularization.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., October, 2024

Integrated Heterogeneous Graph Attention Network for Incomplete Multi-modal Clustering.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., September, 2024

Few-Shot Learning With Multi-Granularity Knowledge Fusion and Decision-Making.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, August, 2024

Multiview Deep Subspace Clustering Networks.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., July, 2024

Exploring and exploiting hierarchical structures for large-scale classification.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., June, 2024

Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking.

[BibT_eX]

[DOI]

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

Discriminative Suprasphere Embedding for Fine-Grained Visual Categorization.

[BibT_eX]

[DOI]

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

Improved generative adversarial network with deep metric learning for missing data imputation.

[BibT_eX]

[DOI]

Neurocomputing, February, 2024

The Image Data and Backbone in Weakly Supervised Fine-Grained Visual Categorization: A Revisit and Further Thinking.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., January, 2024

Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Exploring Diverse Representations for Open Set Recognition.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Every Node Is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Collaborative Decision-Reinforced Self-Supervision for Attributed Graph Clustering.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., December, 2023

OpenMix+: Revisiting Data Augmentation for Open Set Recognition.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., November, 2023

Multi-Granularity Regularized Re-Balancing for Class Incremental Learning.

[BibT_eX]

[DOI]

Huitong Chen

Yu Wang

Qinghua Hu

IEEE Trans. Knowl. Data Eng., July, 2023

Building hierarchical class structures for extreme multi-class learning.

[BibT_eX]

[DOI]

Hongzhi Huang

Yu Wang

Qinghua Hu

Int. J. Mach. Learn. Cybern., July, 2023

Class-Specific Semantic Reconstruction for Open Set Recognition.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Coarse-to-Fine: Progressive Knowledge Transfer-Based Multitask Convolutional Neural Network for Intelligent Large-Scale Fault Diagnosis.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., February, 2023

Latent Heterogeneous Graph Network for Incomplete Multi-View Learning.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2023

Robust Multi-Drone Multi-Target Tracking to Resolve Target Occlusion: A Benchmark.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2023

Dynamic Sub-graph Distillation for Robust Semi-supervised Continual Learning.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Hierarchical Semantic Risk Minimization for Large-Scale Classification.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2022

Multi-granularity episodic contrastive learning for few-shot learning.

[BibT_eX]

[DOI]

Pattern Recognit., 2022

Deep collaborative multi-task network: A human decision process inspired model for hierarchical image classification.

[BibT_eX]

[DOI]

Pattern Recognit., 2022

Uncertainty instructed multi-granularity decision for large-scale hierarchical classification.

[BibT_eX]

[DOI]

Inf. Sci., 2022

Multi-granularity Inter-class Correlation Based Contrastive Learning for Open Set Recognition.

[BibT_eX]

[DOI]

Int. J. Softw. Informatics, 2022

Learning Self-supervised Low-Rank Network for Single-Stage Weakly and Semi-supervised Semantic Segmentation.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2022

RCANet: Row-Column Attention Network for Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

A Recursive Regularization Based Feature Selection Framework for Hierarchical Classification.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2021

PQA-Net: Deep No Reference Point Cloud Quality Assessment via Multi-View Projection.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., 2021

Self-paced hierarchical metric learning (SPHML).

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., 2021

Get to the Point: Content Classification of Animated Graphics Interchange Formats with Key-Frame Attention.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020

Deep Fuzzy Tree for Large-Scale Hierarchical Visual Classification.

[BibT_eX]

[DOI]

Jonathan M. Garibaldi

Xianling Li

IEEE Trans. Fuzzy Syst., 2020

Expert Training: Task Hardness Aware Meta-Learning for Few-Shot Classification.

[BibT_eX]

[DOI]

CoRR, 2020

2018

Deep super-class learning for long-tail distributed image classification.

[BibT_eX]

[DOI]

Yucan Zhou

Qinghua Hu

Yu Wang

Pattern Recognit., 2018

Monotonicity Induced Parameter Learning for Bayesian Networks with Limited Data.

[BibT_eX]

[DOI]

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Monotonicity Extraction for Monotonic Bayesian Networks Parameter Learning.

[BibT_eX]

[DOI]

Jingzhuo Yang

Yu Wang

Qinghua Hu

Proceedings of the Neural Information Processing - 25th International Conference, 2018

2017

Local Bayes Risk Minimization Based Stopping Strategy for Hierarchical Classification.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Yu Wang

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