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个人简介
Research Interests
I am broadly interested in the areas of data mining, machine learning and health informatics, with an emphasize on improving model generalization on complex data. Due to the difficulty in data collection and data annotation process, real-world data (such as health data) are often incomplete, limited and heterogeneous. My work mainly focuses on mitigating the effect of two problems: data missingness and data scarcity. For data missingness, I consider two types of missingness: incomplete modalities in multi-modal learning (IJCAI19'_MeLIM), and missing values in time series analysis (BigData20'_GLIMA).
For the data scarcity issue, my work is based on the meta-learning paradigm. We develop a series of approaches with better generalization performance across domains/tasks for few-shot classification, including cross-domain learning with a single or multiple source domains (to appear), learning with non-stationary task distribution, and meta-learning in several application areas (KDD20'_TAdaNet, UbiComp21'_MetaTP).
I am broadly interested in the areas of data mining, machine learning and health informatics, with an emphasize on improving model generalization on complex data. Due to the difficulty in data collection and data annotation process, real-world data (such as health data) are often incomplete, limited and heterogeneous. My work mainly focuses on mitigating the effect of two problems: data missingness and data scarcity. For data missingness, I consider two types of missingness: incomplete modalities in multi-modal learning (IJCAI19'_MeLIM), and missing values in time series analysis (BigData20'_GLIMA).
For the data scarcity issue, my work is based on the meta-learning paradigm. We develop a series of approaches with better generalization performance across domains/tasks for few-shot classification, including cross-domain learning with a single or multiple source domains (to appear), learning with non-stationary task distribution, and meta-learning in several application areas (KDD20'_TAdaNet, UbiComp21'_MetaTP).
研究兴趣
论文共 30 篇作者统计合作学者相似作者
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引用量
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期刊级别
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CVPR 2023pp.24521-24531, (2023)
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCEno. 12 (2023): 14337-14352
SDMpp.784-792, (2023)
Meta-Learning with Medical Imaging and Health Informatics Applicationspp.253-273, (2023)
International Conference on Machine Learningpp.22985-22998, (2022)
European Conference on Computer Vision (2022): 221-238
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.no. 3 (2021): 1-28
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologiesno. 3 (2021): 1-28
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作者统计
#Papers: 29
#Citation: 833
H-Index: 16
G-Index: 26
Sociability: 4
Diversity: 3
Activity: 11
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