基本信息
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职业迁徙
个人简介
My primary area of research is machine learning, with an emphasis on learning useful data representations, and learning accurate classification models under various circumstances. My research goal is to automate the learning process and reduce the dependence of learning systems on human guidance. Natural language processing, computer vision and bioinformatics are my application areas. My research covers the following topics:
Generalized information adaptation: domain adaptation, cross-lingual learning, zero-shot learning
Weakly supervised learning
Learning with complex outputs: multi-label learning, sequence labeling
Heterogeneous learning: multi-label, multi-view, multi-instance learning
Representation learning: dimensionality reduction and feature selection, deep learning
Active learning
Learning recommender systems
Learning graphical models
Optimization
Generalized information adaptation: domain adaptation, cross-lingual learning, zero-shot learning
Weakly supervised learning
Learning with complex outputs: multi-label learning, sequence labeling
Heterogeneous learning: multi-label, multi-view, multi-instance learning
Representation learning: dimensionality reduction and feature selection, deep learning
Active learning
Learning recommender systems
Learning graphical models
Optimization
研究兴趣
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ICLR 2023 (2023)
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ICLR 2023 (2023)
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)pp.15424-15433, (2023)
FLAIRS (2023)
2023 IEEE International Conference on Knowledge Graph (ICKG) (2023): 1-8
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES: RESEARCH TRACK, ECML PKDD 2023, PT III (2023): 309-324
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