Nan Ye | ARC Centre of Excellence for Mathematical and Statistical Frontiers

Associate Investigator

The University of Queensland

I received my PhD in Computer Science from National University of Singapore, under the supervision of A/P Wee Sun Lee and Prof. Sanjay Jain. Before that, I received double first class honors in Computer Science and Applied Mathematics, also from NUS.

Research Interests:

Graphical models

optimization for big data

planning under uncertainty

Qualifications:

PhD

Projects

Efficient learning and sampling algorithms for big data and complex models

This project aims to develop algorithms and analysis techniques for large scale optimization and sampling problems that arise in machine learning. Some of the main treads are:

Publications

Book Chapters

2019

Ye, N., Roosta-Khorasani F., Cui T., De Gier J., Praeger C. E., & Tao T. (2019). Optimization Methods for Inverse Problems. (Wood, D., Ed.).2017 MATRIX Annals. doi: 10.1007/978-3-030-04161-8_9

Invited talks, refereed proceedings and other conference outputs

2019

Filar, J., Qiao Z., & Ye N. (2019). POMDPs for sustainable fishery management. MODSIM.

[Anonymous] (2019). Algorithms and Models for the Web Graph. (Avrachenkov, K., Prałat P., & Ye N., Ed.).16th International Workshop, WAW 2019. doi: 10.1007/978-3-030-25070-6

2017

Wrigley, A., Lee W. Sun, & Ye N. (2017). Tensor Belief Propagation. International Conference on Machine Learning. 3771–3779.

2016

Ye, N. (2016). Robustness of Bayesian pool-based active learning against prior misspecification. Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16).

Journal Articles

2017

Ye, N., Somani A., Hsu D., & Lee W. Sun (2017). DESPOT: Online POMDP planning with regularization. Journal of Artificial Intelligence Research. 58, 231–266. doi: 10.1613/jair.5328

Mengersen, KL., Peterson E., Clifford S., Ye N., Kim J., Bednarz T., et al. (2017). Modelling imperfect presence data obtained by citizen science. Environmetrics. 28(5), e2446. doi: 10.1002/env.2446

Technical reports and unrefereed outputs

2017

Ye, N., & Bartlett P.L. (2017). Approximate and Stochastic Greedy Optimization.

Research links

ORCID

Contact

nan.ye@uq.edu.au

Welcome to the ACEMS Reportal

All contributors should enter data on all of the Centre’s reportable key performance indicators (KPIs).

Dr Nan Ye

Projects

Efficient learning and sampling algorithms for big data and complex models

Publications

2019

2019

2017

2016

2017

2017

Research links

Contact

Links

ARC Centre of Excellence for Mathematical & Statistical Frontiers

Welcome to the ACEMS Reportal

All contributors should enter data on all of the Centre’s reportable key performance indicators (KPIs).

Dr Nan Ye

2019

2019

2017

2016

2017

2017

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Links

ARC Centre of Excellence for Mathematical & Statistical Frontiers