Xuhui Fan

Orcid: 0000-0002-7558-7200

Affiliations:
  • Macquarie University, Sydney, NSW, Australia
  • University of Newcastle, Australia (former)
  • University of New South Wales, Sydney, NSW, Australia (former)
  • NICTA, Data61, Australia (former)
  • University of Technology Sydney, NSW, Australia (PhD 2015)


According to our database1, Xuhui Fan authored at least 45 papers between 2012 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2023
Dynamic customer segmentation via hierarchical fragmentation-coagulation processes.
Mach. Learn., January, 2023

Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Bayesian Federated Learning: A Survey.
CoRR, 2023

Free-Form Variational Inference for Gaussian Process State-Space Models.
Proceedings of the International Conference on Machine Learning, 2023

2022
Supervised Categorical Metric Learning With Schatten p-Norms.
IEEE Trans. Cybern., 2022

Smoothing graphons for modelling exchangeable relational data.
Mach. Learn., 2022

2021
Kernelized Sparse Bayesian Matrix Factorization.
IEEE Trans. Neural Networks Learn. Syst., 2021

Efficient EM-variational inference for nonparametric Hawkes process.
Stat. Comput., 2021

Decoupling Sparsity and Smoothness in Dirichlet Belief Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Continuous-time edge modelling using non-parametric point processes.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bayesian Nonparametric Space Partitions: A Survey.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures.
IEEE Trans. Signal Process., 2020

Fast multi-resolution segmentation for nonstationary Hawkes process using cumulants.
Int. J. Data Sci. Anal., 2020

Supervised Categorical Metric Learning with Schatten p-Norms.
CoRR, 2020

Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling.
CoRR, 2020

Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Online Binary Space Partitioning Forests.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Fragmentation Coagulation Based Mixed Membership Stochastic Blockmodel.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Image Denoising Based on Nonlocal Bayesian Singular Value Thresholding and Stein's Unbiased Risk Estimator.
IEEE Trans. Image Process., 2019

Scalable Deep Generative Relational Models with High-Order Node Dependence.
CoRR, 2019

Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation.
CoRR, 2019

Binary Space Partitioning Forests.
CoRR, 2019

Hawkes Process with Stochastic Triggering Kernel.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Scalable Deep Generative Relational Model with High-Order Node Dependence.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Binary Space Partitioning Forest.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Refined MISD Algorithm Based on Gaussian Process Regression.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Corrosion Prediction on Sewer Networks with Sparse Monitoring Sites: A Case Study.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Rectangular Bounding Process.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Binary Space Partitioning-Tree Process.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network.
IEEE Trans. Cybern., 2017

2016
Stochastic Patching Process.
CoRR, 2016

Bayesian Optimization of Partition Layouts for Mondrian Processes.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Copula Mixed-Membership Stochastic Blockmodel.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

The Ostomachion Process.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Nonparametric Bayesian models for learning network coupling relationships
PhD thesis, 2015

Dynamic Infinite Mixed-Membership Stochastic Blockmodel.
IEEE Trans. Neural Networks Learn. Syst., 2015

A convergence theorem for graph shift-type algorithms.
Pattern Recognit., 2015

2013
Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models
CoRR, 2013

Non-parametric Power-law Data Clustering.
CoRR, 2013

Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network.
CoRR, 2013

Copula Mixed-Membership Stochastic Blockmodel for Intra-Subgroup Correlations.
CoRR, 2013

2012
Model the complex dependence structures of financial variables by using canonical vine.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Maximum margin clustering on evolutionary data.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

A Theoretical Framework of the Graph Shift Algorithm.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012


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