4 papers
Visualizing Uncertainty: Spatial Maps of Missing and Conflicting Evidence in Deep Learning
Dong Hyun Jeong, Feng Chen, Jin-Hee Cho +3
Understanding when and why deep neural networks are uncertain is crucial for deploying reliable machine learning systems in safety-critical domains. While existing uncertainty quan…
X-MAP: eXplainable Misclassification Analysis and Profiling for Spam and Phishing Detection
Qi Zhang, Dian Chen, Lance M. Kaplan +4
Misclassifications in spam and phishing detection are very harmful, as false negatives expose users to attacks while false positives degrade trust. Existing uncertainty-based detec…
Beyond Binary Opinions: A Deep Reinforcement Learning-Based Approach to Uncertainty-Aware Competitive Influence Maximization
Qi Zhang, Dian Chen, Lance M. Kaplan +4
The Competitive Influence Maximization (CIM) problem involves multiple entities competing for influence in online social networks (OSNs). While Deep Reinforcement Learning (DRL) ha…
Winning the Social Media Influence Battle: Uncertainty-Aware Opinions to Understand and Spread True Information via Competitive Influence Maximization
Qi Zhang, Lance M. Kaplan, Audun Jøsang +3
Competitive Influence Maximization (CIM) involves entities competing to maximize influence in online social networks (OSNs). Current Deep Reinforcement Learning (DRL) methods in CI…