Thursday, 20 October 2022, 5:30pm (HKT) on Zoom
Community detection in the context of social networking has been important research in machine learning and data science. In this talk, Xu will briefly review the recent history of community detection research, starting with the seminal research in stochastic block model and continuing to more complex work such as the Copula-based Mixture Membership Stochastic Block model. He will finish the talk by discussing how these models can help in a journalism setting.
RICHARD YI DA XU is currently a Professor in the Department of Mathematics at Hong Kong Baptist University (HKBU). His research fields are Machine Learning and Artificial Intelligence, and his recent research interests include Bayesian Nonparametric and (machine) Learning Theory. Richard has published papers at many top international conferences, including ICLR, AAAI, IJCAI, ECAI, ECCV, AI-STATS and ICDM, and many top IEEE Transactions: IEEE (TNNLS, TIP, TSP, TKDE, MC and T-Cybernetics). Since 2009, he has created more than 2,000 slides of free machine learning online doctoral training materials and online machine learning videos. During his employment in Australia, his team has collaborated with many Australian industries in finance, e-commerce, government, transport, utilities, defence, agricultural, communication and legal sectors. He established a Deep Learning Sydney meetup which has 4700+ members, one of the largest of its kind in Australia. He represented Australia to attend ISO JTC1 SC42 (Artificial Intelligence)’s first plenary.
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Organised by Research Postgraduate Studies Program, School of Communication