13 citations · 59 across the 11 of their papers we have counts for
5 papers · 1 filter
Unified Classification and Rejection: A One-versus-All Framework
Zhen Cheng, Xu-Yao Zhang, Cheng-Lin Liu
Classifying patterns of known classes and rejecting ambiguous and novel (also called as out-of-distribution (OOD)) inputs are involved in open world pattern recognition. Deep neura…
Towards Trustworthy Dataset Distillation
Shijie Ma, Fei Zhu, Zhen Cheng +1
Efficiency and trustworthiness are two eternal pursuits when applying deep learning in real-world applications. With regard to efficiency, dataset distillation (DD) endeavors to re…
OpenMix: Exploring Outlier Samples for Misclassification Detection
Fei Zhu, Zhen Cheng, Xu-Yao Zhang +1
Reliable confidence estimation for deep neural classifiers is a challenging yet fundamental requirement in high-stakes applications. Unfortunately, modern deep neural networks are…
Rethinking Confidence Calibration for Failure Prediction
Fei Zhu, Zhen Cheng, Xu-Yao Zhang +1
Reliable confidence estimation for the predictions is important in many safety-critical applications. However, modern deep neural networks are often overconfident for their incorre…
Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detection
Zhen Cheng, Fei Zhu, Xu-Yao Zhang +1
Detecting Out-of-distribution (OOD) inputs have been a critical issue for neural networks in the open world. However, the unstable behavior of OOD detection along the optimization…