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Found 3 papers, 1 papers with code
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability
Anomaly detection (AD), also referred to as outlier detection, is a statistical process aimed at identifying observations within a dataset that significantly deviate from the expected pattern of the majority of the data.
Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls
The detection of state-sponsored trolls operating in influence campaigns on social media is a critical and unsolved challenge for the research community, which has significant implications beyond the online realm.
Combining the analytical hierarchy process and the genetic algorithm to solve the timetable problem
The main problems of school course timetabling are time, curriculum, and classrooms.
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