3 papers
cs.LG2023
Certified Interpretability Robustness for Class Activation Mapping
Alex Gu, Tsui-Wei Weng, Pin-Yu Chen +2
Interpreting machine learning models is challenging but crucial for ensuring the safety of deep networks in autonomous driving systems. Due to the prevalence of deep learning based…
cs.LG2022★ 1 cited
Learning from Multiple Annotator Noisy Labels via Sample-wise Label Fusion
Zhengqi Gao, Fan-Keng Sun, Mingran Yang +7
Data lies at the core of modern deep learning. The impressive performance of supervised learning is built upon a base of massive accurately labeled data. However, in some real-worl…
cs.CE2014
Uncertainty Quantification for Integrated Circuits: Stochastic Spectral Methods
Zheng Zhang, Ibrahim, M. Elfadel +1
Due to significant manufacturing process variations, the performance of integrated circuits (ICs) has become increasingly uncertain. Such uncertainties must be carefully quantified…