41 citations · 104 across the 15 of their papers we have counts for
8 papers · 1 filter
Fair-CDA: Continuous and Directional Augmentation for Group Fairness
Rui Sun, Fengwei Zhou, Zhenhua Dong +6
In this work, we propose {\it Fair-CDA}, a fine-grained data augmentation strategy for imposing fairness constraints. We use a feature disentanglement method to extract the feature…
Boosting Out-of-Distribution Detection with Multiple Pre-trained Models
Feng Xue, Zi He, Chuanlong Xie +2
Out-of-Distribution (OOD) detection, i.e., identifying whether an input is sampled from a novel distribution other than the training distribution, is a critical task for safely dep…
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
Qishi Dong, Awais Muhammad, Fengwei Zhou +5
Recent advances on large-scale pre-training have shown great potentials of leveraging a large set of Pre-Trained Models (PTMs) for improving Out-of-Distribution (OoD) generalizatio…
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Muhammad Awais, Fengwei Zhou, Chuanlong Xie +3
Deep neural networks are susceptible to adversarially crafted, small and imperceptible changes in the natural inputs. The most effective defense mechanism against these examples is…
Towards a Theoretical Framework of Out-of-Distribution Generalization
Haotian Ye, Chuanlong Xie, Tianle Cai +3
Generalization to out-of-distribution (OOD) data is one of the central problems in modern machine learning. Recently, there is a surge of attempts to propose algorithms that mainly…
Out-of-Distribution Generalization Analysis via Influence Function
Haotian Ye, Chuanlong Xie, Yue Liu +1
The mismatch between training and target data is one major challenge for current machine learning systems. When training data is collected from multiple domains and the target doma…
MetaAugment: Sample-Aware Data Augmentation Policy Learning
Fengwei Zhou, Jiawei Li, Chuanlong Xie +4
Automated data augmentation has shown superior performance in image recognition. Existing works search for dataset-level augmentation policies without considering individual sample…
Risk Variance Penalization
Chuanlong Xie, Haotian Ye, Fei Chen +3
The key of the out-of-distribution (OOD) generalization is to generalize invariance from training domains to target domains. The variance risk extrapolation (V-REx) is a practical…