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Selected Publications

Journal Articles

  • Yuexuan An, Hui Xue, Xingyu Zhao. Conditional Self-Supervised Learning for Few-Shot Learning. IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2026, in press. [CCF-B]

  • Xingyu Zhao, Lei Qi, Yuexuan An, Xin Geng. Delving into Generalizable Label Distribution Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2025, 47(10): 8708-8724. [CCF-A]

  • Xingyu Zhao, Yuexuan An, Ning Xu, Lei Qi, Xin Geng. Interactive Fusion Label Enhancement for Multi-Label Learning. ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2025, 19(7): 142:1-142:23. [CCF-B]

  • Xingyu Zhao, Yuexuan An, Lei Qi, Xin Geng. Scalable Label Distribution Learning for Multi-Label Classification. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2025, 36(7): 13232-13246. [CAAI-A]

  • Yuexuan An, Hui Xue, Xingyu Zhao, Ning Xu, Pengfei Fang, Xin Geng. Leveraging Bilateral Correlations for Multi-Label Few-Shot Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2025, 36(4): 6816-6828. [CAAI-A]

  • Xingyu Zhao, Yuexuan An, Ning Xu, Xin Geng. Variational Continuous Label Distribution Learning for Multi-Label Text Classification. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024, 36(6): 2716-2729. [CCF-A]

  • Yuexuan An, Hui Xue, Xingyu Zhao, Jing Wang. From Instance to Metric Calibration: A Unified Framework for Open-World Few-Shot Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2023, 45(8): 9757-9773. [CCF-A]

  • Xingyu Zhao, Yuexuan An, Ning Xu, Xin Geng. Continuous Label Distribution Learning. Pattern Recognition (PRJ), 2023, 133: 109056. [CCF-B]

  • Nan Zhang, Shifei Ding, Jian Zhang, Xingyu Zhao. Robust Spike-and-Slab Deep Boltzmann Machines for Face Denoising. Neural Computing and Applications (NCAA), 2020, 32(7): 2815-2827. [CCF-C]

  • Shifei Ding, Xingyu Zhao, Xinzheng Xu, Tongfeng Sun, Weikuan Jia. An Effective Asynchronous Framework for Small Scale Reinforcement Learning Problems. Applied Intelligence (APIN), 2019, 49(12): 4303-4318. [CCF-C]

  • Shifei Ding, Wei Du, Xingyu Zhao, Lijuan Wang, Weikuan Jia. A New Asynchronous Reinforcement Learning Algorithm Based on Improved Parallel PSO. Applied Intelligence (APIN), 2019, 49(12): 4211-4222. [CCF-C]

  • Nan Zhang, Shifei Ding, Jian Zhang, Xingyu Zhao. Deep Belief Network Based on Noisy Data and Clean Data. Journal of Software, 2019, 30(11):3326-3339. (In Chinese) [CCF-T1]

  • Shifei Ding, Peng Du, Xingyu Zhao, Qiangbo Zhu, Yu Xue. BEMD Image Fusion Based on PCNN and Compressed Sensing. Soft Computing (SOCO), 2019, 23(20): 10045-10054. [CCF-C]

  • Weixin Bian, Shifei Ding, Nan Zhang, Jian Zhang, Xingyu Zhao. Combined Filtering and DBM Reconstructing for Fingerprint Enhancement. Journal of Software, 2019, 30(6): 1886-1900. (In Chinese) [CCF-T1]

  • Xingyu Zhao, Shifei Ding, Yuexuan An, Weikuan Jia. Applications of Asynchronous Deep Reinforcement Learning Based on Dynamic Updating Weights. Applied Intelligence (APIN), 2019, 49(2): 581-591. [CCF-C]

  • Shifei Ding, Xingyu Zhao, Jian Zhang, Xiekai Zhang, Yu Xue. A Review on Multi-Class TWSVM. Artificial Intelligence Review, 2019, 52(2): 775-801.

  • Xingyu Zhao, Shifei Ding, Yuexuan An, Weikuan Jia. Asynchronous Reinforcement Learning Algorithms for Solving Discrete Space Path Planning Problems. Applied Intelligence (APIN), 2018, 48(12): 4889-4904. [CCF-C]

  • Xingyu Zhao, Shifei Ding. Research on Deep Reinforcement Learning. Computer Science, 2018, 45(7): 1-6. (In Chinese) [CCF-T2]

  • Shifei Ding, Xingyu Zhao, Hui Xu, Qiangbo Zhu, Yu Xue. NSCT-PCNN Image Fusion Based on Image Gradient Motivation. IET Computer Vision (IET-CVI), 2018, 12(4): 377-383. [CCF-C]

Conference Papers

  • Xingyu Zhao, Lei Qi, Yuexuan An, Xin Geng. Generalizable Label Distribution Learning. In: Proceedings of the 31st ACM International Conference on Multimedia (MM'23), Ottawa, Ontario, Canada, 2023, 8932-8941. [CCF-A]

  • Yuexuan An, Xingyu Zhao, Hui Xue. Learning to Learn from Corrupted Data for Few-Shot Learning. In: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), Macao, China, 2023, 3423-3431. [CAAI-A]

  • Xingyu Zhao, Yuexuan An, Ning Xu, Jing Wang, Xin Geng. Imbalanced Label Distribution Learning. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI'23), Washington, DC, USA, 2023, 11336-11344. (Oral) [CCF-A]

  • Xingyu Zhao, Yuexuan An, Ning Xu, Xin Geng. Fusion Label Enhancement for Multi-Label Learning. In: Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI'22), Vienna, Austria, 2022, 3773-3779. (Long Oral, Acceptance rate 3.7%) [CAAI-A]

  • Yuexuan An, Hui Xue, Xingyu Zhao, Lu Zhang. Conditional Self-Supervised Learning for Few-Shot Classification. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21), Montreal, Quebec, Canada, 2021, 2140-2146. [CAAI-A]

  • Xingyu Zhao, Shifei Ding, Yuexuan An. A New Asynchronous Architecture for Tabular Reinforcement Learning Algorithms. In: Proceedings of the 8nd International Conference on Extreme Learning Machines (ELM'17), Yantai, China, 2017, 172-180.