1 code implementation • 6 Jan 2024 • Shuhao Chen, Yulong Zhang, Weisen Jiang, Jiangang Lu, Yu Zhang
Recent advances achieved by deep learning models rely on the independent and identically distributed assumption, hindering their applications in real-world scenarios with domain shifts.
no code implementations • 23 Sep 2023 • Yulong Zhang, Shuhao Chen, Weisen Jiang, Yu Zhang, Jiangang Lu, James T. Kwok
However, the performance of existing UDA methods is constrained by the large domain shift and limited target domain data.
no code implementations • 17 Mar 2023 • Yulong Zhang, Shuhao Chen, Yu Zhang, Jiangang Lu
The generated samples can well simulate the data distribution of the target domain and help existing UDA methods transfer from the source domain to the target domain more easily, thus improving the transfer performance.
no code implementations • 15 Feb 2020 • Song Liu, Yulong Zhang, Mingxuan Yi, Mladen Kolar
Density Ratio Estimation has attracted attention from the machine learning community due to its ability to compare the underlying distributions of two datasets.
no code implementations • 18 Jun 2019 • Yao-Hui Chen, Peng Li, Jun Xu, Shengjian Guo, Rundong Zhou, Yulong Zhang, Taowei, Long Lu
Unlike the existing hybrid testing tools, SAVIOR prioritizes the concolic execution of the seeds that are likely to uncover more vulnerabilities.
Software Engineering