Machine Learning

Real-Time Prediction of Online False Information Purveyors and their Characteristics

Abstract Disinformation, misinformation, and other `fake news’ – collectively false information is quick and inexpensive to create and distribute in our increasingly digital and connected world. Identifying false information early and cost effectively can offset some of those operational advantages. In this paper, we develop light-weight machine learning models that utilize (1) a novel data

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Simon Lucey

Australian Institute for Machine Learning (AIML), University of Adelaide My research is motivated from a passion for discovering the “why?” behind “how?” with respect to core problems in Artificial Intelligence, Computer Vision and Machine Learning. I am currently leading the CI2CV laboratory, newly re-located to the Robotics Institute, Carnegie Mellon University in Pittsburgh, PA, USA where we

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The Future of IT Audit

ISACA’s The Future of IT Audit: Research Brief reveals the opportunities and challenges that
await the IT audit professional and sheds light on the IT audit profession in general. In this paper,
ISACA presents survey findings related to the involvement of auditors in technology projects
within their enterprise, the technology challenges faced by auditors, the perceived impact of
automation and artificial intelligence (AI), and the IT audit staffing implications and workforce
development issues caused by new technologies.

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