no code implementations • 27 Sep 2023 • Eva Riherd, Raghu Mudumbai, Weiyu Xu
We propose a general method for semantic representation of images and other data using progressive coding.
no code implementations • 5 Aug 2020 • Jirong Yi, Myung Cho, Xiaodong Wu, Raghu Mudumbai, Weiyu Xu
In this paper, we consider the problem of designing optimal pooling matrix for group testing (for example, for COVID-19 virus testing) with the constraint that no more than $r>0$ samples can be pooled together, which we call "dilution constraint".
no code implementations • 28 Jul 2020 • Jirong Yi, Raghu Mudumbai, Weiyu Xu
We consider the theoretical problem of designing an optimal adversarial attack on a decision system that maximally degrades the achievable performance of the system as measured by the mutual information between the degraded signal and the label of interest.
no code implementations • 26 Mar 2020 • Zain Khan, Jirong Yi, Raghu Mudumbai, Xiaodong Wu, Weiyu Xu
Recent works have demonstrated the existence of {\it adversarial examples} targeting a single machine learning system.
no code implementations • 27 Jan 2019 • Hui Xie, Jirong Yi, Weiyu Xu, Raghu Mudumbai
We present a simple hypothesis about a compression property of artificial intelligence (AI) classifiers and present theoretical arguments to show that this hypothesis successfully accounts for the observed fragility of AI classifiers to small adversarial perturbations.