Kun Wang

According to our database, Kun Wang authored at least 11 papers between 2020 and 2025.

Collaborative distances:

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

2025

Drift-aware Collaborative Assistance Mixture of Experts for Heterogeneous Multistream Learning.

En Yu, Jie Lu, Kun Wang, Xiaoyu Yang, Guangquan Zhang

CoRR, August, 2025

An evolutionary game approach for information sharing within medical consortium based on complex network.

Rudan Xue, Li Xiong, Kun Wang

Comput. Ind. Eng., 2025

2024

TS-DM: A Time Segmentation-Based Data Stream Learning Method for Concept Drift Adaptation.

Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang

IEEE Trans. Cybern., October, 2024

A self-adaptive ensemble for user interest drift learning.

Kun Wang, Li Xiong, Anjin Liu, Guangquan Zhang, Jie Lu

Neurocomputing, 2024

A Neighbor-Searching Discrepancy-based Drift Detection Scheme for Learning Evolving Data.

Feng Gu, Jie Lu, Zhen Fang, Kun Wang, Guangquan Zhang

CoRR, 2024

2023

Evolving Gradient Boost: A Pruning Scheme Based on Loss Improvement Ratio for Learning Under Concept Drift.

Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang, Li Xiong

IEEE Trans. Cybern., April, 2023

TCR-M: A Topic Change Recognition-based Method for Data Stream Learning.

Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 27th International Conference KES-2023, 2023

An Augmented Learning Approach for Multiple Data Streams Under Concept Drift.

Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang

Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023

2022

Elastic gradient boosting decision tree with adaptive iterations for concept drift adaptation.

Kun Wang, Jie Lu, Anjin Liu, Yiliao Song, Li Xiong, Guangquan Zhang

Neurocomputing, 2022

2020

Fast Switch Naïve Bayes to Avoid Redundant Update for Concept Drift Learning.

Anjin Liu, Guangquan Zhang, Kun Wang, Jie Lu

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

An Elastic Gradient Boosting Decision Tree for Concept Drift Learning.

Kun Wang, Anjin Liu, Jie Lu, Guangquan Zhang, Li Xiong

Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020