9 citations · 26 across the 20 of their papers we have counts for
5 papers · 1 filter
Data Optimization in Deep Learning: A Survey
Ou Wu, Rujing Yao
Large-scale, high-quality data are considered an essential factor for the successful application of many deep learning techniques. Meanwhile, numerous real-world deep learning task…
Combining Adversaries with Anti-adversaries in Training
Xiaoling Zhou, Nan Yang, Ou Wu
Adversarial training is an effective learning technique to improve the robustness of deep neural networks. In this study, the influence of adversarial training on deep learning mod…
Rethinking Class Imbalance in Machine Learning
Ou Wu
Imbalance learning is a subfield of machine learning that focuses on learning tasks in the presence of class imbalance. Nearly all existing studies refer to class imbalance as a pr…
Implicit Counterfactual Data Augmentation for Robust Learning
Xiaoling Zhou, Ou Wu, Michael K. Ng
Machine learning models are prone to capturing the spurious correlations between non-causal attributes and classes, with counterfactual data augmentation being a promising directio…
Understanding Difficulty-based Sample Weighting with a Universal Difficulty Measure
Xiaoling Zhou, Ou Wu, Weiyao Zhu +1
Sample weighting is widely used in deep learning. A large number of weighting methods essentially utilize the learning difficulty of training samples to calculate their weights. In…