Yuhong GuoProfessor

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