1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
Contrastive Conditional Alignment based on Label Shift Calibration for Imbalanced Domain Adaptation
Xiaona Sun, Zhenyu Wu, Zhiqiang Zhan +1
Many existing unsupervised domain adaptation (UDA) methods primarily focus on covariate shift, limiting their effectiveness in imbalanced domain adaptation (IDA) where both covaria…
cs.LG2023
centroIDA: Cross-Domain Class Discrepancy Minimization Based on Accumulative Class-Centroids for Imbalanced Domain Adaptation
Xiaona Sun, Zhenyu Wu, Yichen Liu +3
Unsupervised Domain Adaptation (UDA) approaches address the covariate shift problem by minimizing the distribution discrepancy between the source and target domains, assuming that…
cs.LG2023★ 1 cited
Dual-Branch Temperature Scaling Calibration for Long-Tailed Recognition
Jialin Guo, Zhenyu Wu, Zhiqiang Zhan +1
The calibration for deep neural networks is currently receiving widespread attention and research. Miscalibration usually leads to overconfidence of the model. While, under the con…