研究方向是面向开放环境下大数据的自主学习，包括基于复杂多模态数据的稳健学习和基于动态演化数据的可适增量学习。论文发表于TPAMI、TKDE、NeurIPS、KDD等计算机国际顶级期刊和会议50余篇。
Selected Publications:
Yang Yang, Hongpeng Pan, Qing-Yuan Jiang, Yi Xu, and Jinghui Tang. Learning to Rebalance Multi-Modal Optimization by Adaptively Masking Subnetworks. IEEE TPAMI, 2025. (CCF-A)
Yang Yang, Nan Jiang, Yi Xu, De-Chuan Zhan. Robust Semi-supervised Learning by Wisely Leveraging Open-set Data. IEEE TPAMI, 2024. (CCF-A)
Yang Yang, Chubing Zhang, Xin Song, Zheng Dong, Hengshu Zhu, Wenjie Li. Contextualized Knowledge Graph Embedding for Explainable Talent Training Course Recommendation. (ACM TOIS), 2023. (CCF-A)
Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang, Jian Yang. Cost-Effective Incremental Deep Model: Matching Model Capacity with The Least Sampling. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2022. (CCF-A)
Yang Yang, Zhen-Qiang Sun, Hengshu Zhu, Yanjie Fu, Yuanchun Zhou, Hui Xiong, Jian Yang. Learning Adaptive Embedding Considering Incremental Class. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021. (CCF-A)
Yang Yang, Jia-Qi Yang, Ran Bao, De-Chuan Zhan, Hengshu Zhu, Xiao-Ru Gao, Hui Xiong, Jian Yang. Corporate Relative Valuation using Heterogeneous Multi-Modal Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021. (CCF-A).
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