Projects per year
Personal profile
Chinese Name
Biography
Richard Yi Da Xu is currently a Full 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 Bayeisan 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 was representing Australia to attend ISO JTC1 SC42 (Artificial Intelligence)’s first plenary.
Research Interests
Learning Theory, Bayesian Nonparametrics, Machine Learning applications
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
PhD, Computer Sciences, University of Technology Sydney
1 Feb 2002 → 31 Dec 2005
Award Date: 10 May 2006
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Collaborations and top research areas from the last five years
Projects
- 2 Active
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Nonlinear Eigen-Approach for Optimization on Stiefel Manifolds Arising from Machine Learning
1/01/23 → …
Project: Research project
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A decision support system in precision medicine: Contrastive multimodal learning for patient stratification
Yin, Q., Zhong, L., Song, Y., Bai, L., Wang, Z., Chen, L., Xu, Y. & Yang, X., 29 Aug 2023, (E-pub ahead of print) In: Annals of Operations Research. 29 p.Research output: Contribution to journal › Journal article › peer-review
Open Access -
Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection
Huang, W., Liu, C., Chen, Y., Xu, R. Y. D., Zhang, M. & Weng, T. W., May 2023, In: Transactions on Machine Learning Research. 30 p.Research output: Contribution to journal › Journal article › peer-review
Open Access -
Domain Decorrelation with Potential Energy Ranking
Pei, S., Sun, J., Xu, R. Y. D., Xiang, S. & Meng, G., 27 Jun 2023, Proceedings of 37th AAAI Conference on Artificial Intelligence, AAAI 2023. Williams, B., Chen, Y. & Neville, J. (eds.). 1st ed. Washington, DC: AAAI press, p. 2020-2028 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 37, no. 2).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access -
Robust Feature Rectification of Pretrained Vision Models for Object Recognition
Zhou, S., Meng, G., Zhang, Z., Xu, R. Y. D. & Xiang, S., 27 Jun 2023, Proceedings of 37th AAAI Conference on Artificial Intelligence, AAAI 2023. Williams, B., Chen, Y. & Neville, J. (eds.). 1st ed. Washington, DC: AAAI press, p. 3796-3804 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 37, no. 3).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access -
Environment-Robust WiFi-based Human Activity Recognition using Enhanced CSI and Deep Learning
Shi, Z., Cheng, Q., Zhang, J. A. & Xu, R. Y. D., 15 Dec 2022, In: IEEE Internet of Things Journal. 9, 24, p. 24643-24654 12 p.Research output: Contribution to journal › Journal article › peer-review
6 Citations (Scopus)