Wavelet twin support vector machines based on glowworm swarm optimization. - Shifei Ding; Yuexuan An; Xiekai Zhang; Fulin Wu; Yu Xue 004 (Neurocomputing, 2017)

Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification. - Shifei Ding; Xiekai Zhang; Yuexuan An; Yu Xue 004 (Pattern Recognit., 2017)

Asynchronous reinforcement learning algorithms for solving discrete space path planning problems. - Xingyu Zhao 002; Shifei Ding; Yuexuan An; Weikuan Jia (Appl. Intell., 2018)

孪生支持向量机综述 (Twin Support Vector Machine: A Review). - Yuexuan An; Shifei Ding; Jipu Hu (计算机科学, 2018)

Discrete space reinforcement learning algorithm based on support vector machine classification. - Yuexuan An; Shifei Ding; Songhui Shi; Jingcan Li (Pattern Recognit. Lett., 2018)

Applications of asynchronous deep reinforcement learning based on dynamic updating weights. - Xingyu Zhao 002; Shifei Ding; Yuexuan An; Weikuan Jia (Appl. Intell., 2019)

Multiple Birth Support Vector Machine with Triplet Loss Function. - Shi-Fei Ding; Yuexuan An (J. Inf. Sci. Eng., 2019)

Multiple birth support vector machine based on recurrent neural networks. - Shifei Ding; Yuting Sun; Yuexuan An; Weikuan Jia (Appl. Intell., 2020)

Conditional Self-Supervised Learning for Few-Shot Classification. - Yuexuan An; Hui Xue 002; Xingyu Zhao 002; Lu Zhang (IJCAI, 2021)

Fusion Label Enhancement for Multi-Label Learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Xin Geng 001 (IJCAI, 2022)

Indefinite twin support vector machine with DC functions programming. - Yuexuan An; Hui Xue 002 (Pattern Recognit., 2022)

Imbalanced Label Distribution Learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Jing Wang 113; Xin Geng 001 (AAAI, 2023)

Learning to Learn from Corrupted Data for Few-Shot Learning. - Yuexuan An; Xingyu Zhao 002; Hui Xue 002 (IJCAI, 2023)

Boosting Few-Shot Open-Set Recognition with Multi-Relation Margin Loss. - Yongjuan Che; Yuexuan An; Hui Xue 002 (IJCAI, 2023)

Generalizable Label Distribution Learning. - Xingyu Zhao 002; Lei Qi 001; Yuexuan An; Xin Geng 001 (ACM Multimedia, 2023)

Continuous label distribution learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Xin Geng 001 (Pattern Recognit., 2023)

From Instance to Metric Calibration: A Unified Framework for Open-World Few-Shot Learning. - Yuexuan An; Hui Xue 002; Xingyu Zhao 002; Jing Wang 113 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Dynamic functional connections analysis with spectral learning for brain disorder detection. - Yanfang Xue; Hui Xue 002; Pengfei Fang; Shipeng Zhu; Lishan Qiao; Yuexuan An (Artif. Intell. Medicine, 2024)

Towards Few-Shot Learning in the Open World: A Review and Beyond. - Hui Xue 002; Yuexuan An; Yongchun Qin; Wenqian Li; Yixin Wu; Yongjuan Che; Pengfei Fang; Minling Zhang (CoRR, 2024)

Reinforced Self-Supervised Training for Few-Shot Learning. - Zhichao Yan; Yuexuan An; Hui Xue 002 (IEEE Signal Process. Lett., 2024)

Variational Continuous Label Distribution Learning for Multi-Label Text Classification. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Xin Geng 001 (IEEE Trans. Knowl. Data Eng., 2024)

Learning Noisy Few-Shot Classification Without Relying on Pseudo-Noise Data. - Yixin Wu; Hui Xue 002; Yuexuan An; Pengfei Fang (IEEE Signal Process. Lett., 2025)

Leveraging Bilateral Correlations for Multi-Label Few-Shot Learning. - Yuexuan An; Hui Xue 002; Xingyu Zhao 002; Ning Xu 009; Pengfei Fang; Xin Geng 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Scalable Label Distribution Learning for Multi-Label Classification. - Xingyu Zhao 002; Yuexuan An; Lei Qi 001; Xin Geng 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Interactive Fusion Label Enhancement for Multi-Label Learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Lei Qi 001; Xin Geng 001 (ACM Trans. Knowl. Discov. Data, 2025)