Representation learning via serial robust autoencoder for domain adaptation

Shuai Yang, Yuhong Zhang, Hao Wang, Peipei Li, Xuegang Hu

Abstract: Highlights•A novel serial robust autoencoder is designed for domain adaptation.•We design two novel autoencoder models and connect them in series to learn effective representations.•We design an iterative approach to solve the proposed GRA model, and prove its convergence.