15 citations · 67 across the 10 of their papers we have counts for
5 papers · 1 filter
Explaining Deep Learning Models - A Bayesian Non-parametric Approach
Wenbo Guo, Sui Huang, Yunzhe Tao +2
Understanding and interpreting how machine learning (ML) models make decisions have been a big challenge. While recent research has proposed various technical approaches to provide…
Towards Interrogating Discriminative Machine Learning Models
Wenbo Guo, Kaixuan Zhang, Lin Lin +2
It is oftentimes impossible to understand how machine learning models reach a decision. While recent research has proposed various technical approaches to provide some clues as to…
Learning Adversary-Resistant Deep Neural Networks
Qinglong Wang, Wenbo Guo, Kaixuan Zhang +4
Deep neural networks (DNNs) have proven to be quite effective in a vast array of machine learning tasks, with recent examples in cyber security and autonomous vehicles. Despite the…
Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks
Qinglong Wang, Wenbo Guo, Alexander G. Ororbia +6
Deep neural networks have proven to be quite effective in a wide variety of machine learning tasks, ranging from improved speech recognition systems to advancing the development of…
Adversary Resistant Deep Neural Networks with an Application to Malware Detection
Qinglong Wang, Wenbo Guo, Kaixuan Zhang +4
Beyond its highly publicized victories in Go, there have been numerous successful applications of deep learning in information retrieval, computer vision and speech recognition. In…