Guojun Gan — accepted AI-conference papers

2020

Maintaining Discrimination and Fairness in Class Incremental Learning

Bowen Zhao, Xi Xiao, Guojun Gan, Bin Zhang, Shu-Tao Xia

CVPR 2020poster

Deep neural networks (DNNs) have been applied in class incremental learning, which aims to solve common real-world problems of learning new classes continually. One drawback of standard DNNs is that they are prone to catastrophic forgetting. Knowledge distillation (KD) is a commonly used technique t…

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2020

Self-Paced Probabilistic Principal Component Analysis For Data With Outliers

Bowen Zhao, Xi Xiao, Wanpeng Zhang, Bin Zhang, Guojun Gan, Shutao Xia

ICASSP 2020accepted

Principal Component Analysis (PCA) is a popular tool for dimension reduction and feature extraction in data analysis. Probabilistic PCA (PPCA) extends the standard PCA by using a probabilistic model. However, both standard PCA and PPCA are not robust, as they are sensitive to outliers. To alleviate…

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