no code implementations • 7 Nov 2020 • Jun Wen, Changjian Shui, Kun Kuang, Junsong Yuan, Zenan Huang, Zhefeng Gong, Nenggan Zheng
To address this issue, we intervene in the learning of feature discriminability using unlabeled target data to guide it to get rid of the domain-specific part and be safely transferable.
no code implementations • 24 Jun 2019 • Jun Wen, Nenggan Zheng, Junsong Yuan, Zhefeng Gong, Changyou Chen
By imposing distribution matching on both features and labels (via uncertainty), label distribution mismatching in source and target data is effectively alleviated, encouraging the classifier to produce consistent predictions across domains.
no code implementations • 12 Nov 2018 • Jun Wen, Risheng Liu, Nenggan Zheng, Qian Zheng, Zhefeng Gong, Junsong Yuan
In this paper, we present a method for learning domain-invariant local feature patterns and jointly aligning holistic and local feature statistics.