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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
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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Network
Projects
- 1 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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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 › Article › peer-review
2 Citations (Scopus) -
Time-varying neural network for stock return prediction
Wong, S. Y. K., Chan, J. S. K., Azizi, L. & Xu, R. Y. D., Jan 2022, In: Intelligent Systems in Accounting, Finance and Management. 29, 1, p. 3-18 16 p.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Gaussian process latent variable model factorization for context-aware recommender systems
Huang, W. & Xu, R. Y. D., Nov 2021, In: Pattern Recognition Letters. 151, p. 281-287 7 p.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Kernelized Sparse Bayesian Matrix Factorization
Li, C., Xie, H-B., Fan, X., Xu, R. Y. D., Huffel, S. V. & Mengersen, K., 23 Mar 2020, In: IEEE Transactions on Neural Networks and Learning Systems. 32, 1, p. 391 - 404Research output: Contribution to journal › Article › peer-review
3 Citations (Scopus) -
Mean field theory for deep dropout networks: Digging up gradient backpropagation deeply
Huang, W., Xu, R. Y. D., Du, W., Zeng, Y. & Zhao, Y., 24 Aug 2020, ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings. De Giacomo, G., Catala, A., Dilkina, B., Milano, M., Barro, S., Bugarin, A. & Lang, J. (eds.). IOS Press BV, p. 1215-1222 8 p. (Frontiers in Artificial Intelligence and Applications; vol. 325).Research output: Chapter in book/report/conference proceeding › Conference contribution › peer-review
Open Access1 Citation (Scopus)