Jing Wang

Orcid: 0000-0003-2734-7138

Affiliations:

Southeast University, School of Computer Science and Engineering, Nanjing, China

According to our database¹, Jing Wang authored at least 27 papers between 2019 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2025

Instance-Dependent Inaccurate Label Distribution Learning.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., January, 2025

Residual k-Nearest Neighbors Label Distribution Learning.

[BibT_eX]

[DOI]

Pattern Recognit., 2025

Progressive label enhancement.

[BibT_eX]

[DOI]

Pattern Recognit., 2025

2024

Large Margin Weighted k-Nearest Neighbors Label Distribution Learning for Classification.

[BibT_eX]

[DOI]

Jing Wang

Xin Geng

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

Inaccurate Label Distribution Learning.

[BibT_eX]

[DOI]

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

Driver distraction detection using semi-supervised lightweight vision transformer.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2024

Redefining in Dictionary: Towards a Enhanced Semantic Understanding of Creative Generation.

[BibT_eX]

[DOI]

CoRR, 2024

Towards Better Performance in Incomplete LDL: Addressing Data Imbalance.

[BibT_eX]

[DOI]

CoRR, 2024

FINE: Factorizing Knowledge for Initialization of Variable-sized Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2024

KIND: Knowledge Integration and Diversion in Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2024

WAVE: Weight Template for Adaptive Initialization of Variable-sized Models.

[BibT_eX]

[DOI]

CoRR, 2024

Inaccurate Label Distribution Learning with Dependency Noise.

[BibT_eX]

[DOI]

CoRR, 2024

Transferring Core Knowledge via Learngenes.

[BibT_eX]

[DOI]

Fu Feng

Jing Wang

Xin Geng

CoRR, 2024

Exploiting Multi-Label Correlation in Label Distribution Learning.

[BibT_eX]

[DOI]

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

2023

From Instance to Metric Calibration: A Unified Framework for Open-World Few-Shot Learning.

[BibT_eX]

[DOI]

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

Label Distribution Learning by Exploiting Label Distribution Manifold.

[BibT_eX]

[DOI]

Jing Wang

Xin Geng

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

RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Inter-label Correlations.

[BibT_eX]

[DOI]

Kouzhiqiang Yucheng Xie

CoRR, 2023

Manipulating the Label Space for In-Context Classification.

[BibT_eX]

[DOI]

CoRR, 2023

Exploiting Multi-Label Correlation in Label Distribution Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Genes in Intelligent Agents.

[BibT_eX]

[DOI]

CoRR, 2023

Data Augmentation For Label Enhancement.

[BibT_eX]

[DOI]

CoRR, 2023

Imbalanced Label Distribution Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Re-Weighting Large Margin Label Distribution Learning for Classification.

[BibT_eX]

[DOI]

Jing Wang

Xin Geng

Hui Xue

IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021

Learn the Highest Label and Rest Label Description Degrees.

[BibT_eX]

[DOI]

Jing Wang

Xin Geng

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Label Distribution Learning Machine.

[BibT_eX]

[DOI]

Jing Wang

Xin Geng

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

Classification with Label Distribution Learning.

[BibT_eX]

[DOI]

Jing Wang

Xin Geng

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Theoretical Analysis of Label Distribution Learning.

[BibT_eX]

[DOI]

Jing Wang

Xin Geng

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Jing Wang

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