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<!DOCTYPE html><!DOCTYPE html>
<html>
<meta name="description" content="Nan Ye's Homepage">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
<meta name="keywords" content="Ye Nan, Nan Ye, machine learning, planning under uncertainty, POMDP, sequential decision making">
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<title>Nan Ye's Homepage</title>
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<body style="background-color:#EEEEEE; margin: 0px">
<!-- Menu bar -->
<div style="width:100%; position: fixed; background-color:black; padding-top: 5px; padding-bottom: 5px">
<table style="width:61vw; margin: auto">
<tr>
<td align="center"><a class="menuitem about-button">About</a></td>
<td align="center"><a class="menuitem group-button">Group</a></td>
<td align="center"><a class="menuitem research-button">Research</a></td>
<td align="center"><a class="menuitem teaching-button">Teaching</a></td>
</tr>
</table>
</div>
<!-- Header -->
<!--div id=header align="center">
<br>
<br>
<table width="850px">
<tr>
<td valign=top>
<br>
<div><b><font size="4">Nan Ye (叶楠)</font></b></div>
<br>
<div class="info">
Lecturer (Statistics & Data Science) <br>
School of Mathematics and Physics<br>
University of Queensland<br>
<br>
<b>Office</b>:
Room 616, Building 69<br>
<b>Phone</b>: +61 (0)70 3346 9095<br>
<b>Email</b>: nan.ye AT uq DOT edu DOT AU<br>
<b>Address:</b>
St Lucia, QLD 4067, Australia
</div>
</td>
<td align="right">
<img src="yn.jpg" height=190>
</td>
</tr>
</table>
<hr>
</div--!>
<div class=content style="background-color:white; border: 1px gray">
<div class="sectioncontent" id="about">
<br><br>
<div style="width:100%">
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<div>
<table style="width:100%" border=0pt>
<tr>
<td style="width:23%">
<div style="width:100%">
<img style="border-radius:50%; width:100%" src="yn.jpg">
</div>
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<td style="width:7%"></td>
<td style="width:70%">
<div style="font-size:12pt">
<b style="font-size:20pt">Nan Ye (叶楠)</b><br><br>
Senior Lecturer (Statistics & Data Science) <br>
School of Mathematics and Physics<br>
University of Queensland<br>
<br>
<b>Office</b>:
Room 616, Building 69<br>
<b>Phone</b>: +61 7 3346 9095<br>
<b>Email</b>: nan.ye AT uq DOT edu DOT AU<br>
<b>Address:</b>
St Lucia, QLD 4067, Australia
</div>
</td>
</tr>
</table>
</div>
</div>
<br><br>
<div>
I am a Senior Lecturer in Statistics and Data Science in the School of Mathematics and Physics in
University of Queensland.
I previously held postdoc positions at QUT and UC Berkeley from 2015 to
2018, and at NUS from 2013 to 2014.
Before that, I earned my PhD in Computer Science from NUS, and completed
double first-class honors in Computer Science and Applied Mathematics, also from
NUS.
</div>
<br>
<div>
I am broadly interested in machine learning algorithms, theory, and applications.
I have published papers on topics including
sequential decision making under uncertainty,
weakly supervised learning,
probabilistic graphical models,
statistical learning theory, in venues such as NeurIPS, ICML, ICLR, UAI,
JAIR, JMLR.
I have received an IJCAI-JAIR Best Paper Prize in 2022, and a UAI Best Student
Paper Award in 2014.
</div>
<br>
<div>
I am seeking highly motivated students to work with me on machine learning
research.
If you are interested, please email me your CV/transcripts, a sample of
your writing, and a brief description of your research interests.
</div>
<h3 class=sectiontitle>News</h3>
<b>2023</b>
<ul>
<li> [07/09] Our paper on a Bayesian method that is robust against prior misspecification is accepted at Computational Statistics.
[<a href="https://link.springer.com/content/pdf/10.1007/s00180-023-01390-0.pdf">PDF</a>]
<li> [06/20] Our paper on a continuous POMDP solver is accepted by IJRR.
[<a href="https://arxiv.org/pdf/2302.10439.pdf">PDF</a>]
<li> [06/06] I am serving AAAI'23 as an SPC member.
<li> [06/02] Our paper on an accelerated ALS algorithm is accepted by NLA.
[<a href="https://onlinelibrary.wiley.com/doi/pdf/10.1002/nla.2516">PDF</a>]
<li> [04/17] I am serving NeurIPS'23 as a reviewer.
<li> [04/17] Our paper on a model-based offline reinforcement learning approach for sustainable fishery management is accepted by Expert Systems.
[<a href="https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13324">PDF</a>]
<li> [02/08] I gave a tutorial on machine learning for applied mathematicians in ANZIAM'23.
[<a href="talks/anziam23/index.html">slides</a>]
</ul>
<b>2022</b>
<ul>
<li>[11/29] I will give a tutorial on machine learning for
applied mathematicians in ANZIAM'23.
<li>[11/28] I am serving IJCAI'23 as an SPC member.
<li>[09/15] Our paper on random forests for positive-unlabeled
learning is accepted by NeurIPS.
[<a href="">PDF</a>]
<li>[07/28] Our paper <i>DESPOT: Online POMDP Planning with
Regularization</i> received the 2022
<a href="https://jair.org/index.php/jair/IJCAIJAIR">IJCAI-JAIR Best Paper Prize</a>.
<li>[08/19] We are organising a
<a href="https://resource-cms.springernature.com/springer-cms/rest/v1/content/23328178/data/v1">Special
Issue of the Annals of Operations Research</a>
on Decision Making Under Uncertainty and calling for papers.
<li>[07/20] I am serving as an organising committee member for
<a href="https://smp.uq.edu.au/anziam-2023">ANZIAM'23</a>.
<li>[07/19] I am serving AAAI'23 as an SPC member.
<li>[05/12] We are organizing a
<a href="https://dmuu2022.github.io/workshop_index.html">Workshop on
Decision Making under Uncertainty</a> and calling for participation.
<li>[22/04] I am selected as a
<a href="https://iclr.cc/Conferences/2022/Reviewers">Highlighted Reviewer</a> for ICLR'22.
<li>[04/01] Our paper on solving continuous-action POMDPs is accepted at WAFR'23.
[<a href="">PDF</a>]
</ul>
</div>
<div class="sectioncontent" id="group">
<h3 class=sectiontitle>Group members</h3>
<b>Current members</b>
<ul>
<li>Marcus Hoerger (Postdoc)
<li>Jun Ju (PhD)
<li>Yeming Lei (PhD)
<li>Jonathan Wilton (PhD)
</ul>
<b>Past members</b>
<ul>
<li><a href="https://graduate-school.uq.edu.au/profile/650/aaron">Aaron Snoswell</a> (PhD, 2022)</li>
<li> Tan Nguyen (PhD, 2020)</li>
<li> Piyush Patil (Masters, 2021)</li>
<li> Cameron Gordon (Masters, 2020)</li>
<li> Yuting Yang (Masters, 2020)</li>
<li> Yutong Chen (Masters, 2020)</li>
<li> Robert Wall (Masters, 2019)</li>
<li> David Evans (Masters, 2019)</li>
<li> Jacky Xie (Honours, 2022)</li>
<li> Montana Wickens (Honours, 2022)</li>
<li> David Maine (Honours, 2021)</li>
<li> Daniel Noar (Honours, 2020)</li>
<li> Scott Whittington (Honours, 2020)</li>
<li> Naziah Saddique (Honours, 2020)</li>
<li> Drew Mitchell (Honours, 2018)</li>
</ul>
</div>
<div class="sectioncontent" id="research">
<h3 class="sectiontitle">Software</h3>
<ul>
<li>
<a href="https://github.com/AdaCompNUS/despot">DESPOT</a>
- Online solver for large POMDPs.
</li>
<li>
<a href="https://github.com/aaronsnoswell/unimodal-irl">MaxEntIRL</a>
- Maximum Entropy IRL.
</a>
<li>
<a href="https://github.com/jonathanwilton/PUExtraTrees">PUExtraTrees</a>
- Extra Trees for PU-learning.
</li>
<li>
<a href="https://github.com/nvcuong/HOSemiCRF">HOSemiCRF</a>
- High-order Semi-Markov Conditional Random Field.
</a>
</li>
</ul>
<h3 class="sectiontitle">Publications</h3>
Please see my
<a href="https://scholar.google.com/citations?user=5XCxGRIAAAAJ&hl=en">Google Scholar profile</a>
for the full list of my publications.
<ul style="font-size:12pt">
<li>
<span class="paper">Positive-unlabeled learning using random forests via recursive greedy risk minimization.</span>
<br>
Jonathan Wilton, Abigail MY Koay, Ryan KL Ko, Miao Xu, and Nan Ye.
<br>
In Advances In Neural Information Processing Systems, 2022
</li>
<li>
<span class="paper">Adaptive Discretization using Voronoi Trees for Continuous-Action POMDPs.</span>
<br>
Marcus Hoerger, Hanna Kurniawati, Dirk Kroese, and Nan Ye.
<br>
In WAFR, 2022
</li>
<li>
<span class="paper">Prior versus data: A new Bayesian method for fishery stock assessment.</span>
<br>
Yeming Lei, Shijie Zhou, and Nan Ye.
<br>
In MODSIM, 2021
</li>
<li>
<span class="paper">MOOR: Model-based Offline Reinforcement Learning for Sustainable Fishery Management.</span>
<br>
Jun Ju, Hanna Kurniawati, Dirk Kroese, and Nan Ye.
<br>
In MODSIM, 2021
</li>
<li>
<span class="paper">Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms. </span>
<br>
Aaron J. Snoswell, Surya P. N. Singh, and Nan Ye.
<br>
In IEEE Symposium Series on Compu- tational Intelligence, 2020.
</li>
<li>
Greedy Convex Ensemble.
<br>
Thanh Tan Nguyen, Nan Ye, and Peter Bartlett.
<br>
In IJCAI, 2020.
</li>
<li>
Discriminative particle filter reinforcement learning for complex partial observations.
<br>
Xiao Ma, Peter Karkus, David Hsu, Wee Sun Lee, and Nan Ye.
<br>
In ICLR, 2020.
</li>
<li>
Nesterov acceleration of alternating least squares for canonical tensor decomposition: Momentum step size selection and restart mechanisms.
<br>
Drew Mitchell, Nan Ye, and Hans De Sterck.
<br>
Numerical Linear Algebra with Applications, 2020.
</li>
<li>
Reading Both Single and Multiple Digital Video Clocks Using Context-Aware Pixel Periodicity and Deep Learning.
<br>
Xinguo Yu, Wu Song, Xiaopan Lyu, Bin He, and Nan Ye.
<br>
International Journal of Digital Crime and Forensics (IJDCF), 12(2):21–39, 2020.
</li>
<li>
POMDPs for sustainable fishery management.
<br>
Jerzy A Filar, Zhihao Qiao, and Nan Ye.
<br>
In International Congress on Modelling and Simulation, 2019.
</li>
<li>
A Framework for Solving Explicit Arithmetic Word Problems and Proving Plane Geometry Theorems.
<br>
Xinguo Yu, Mingshu Wang, Wenbin Gan, Bin He, and Nan Ye.
<br>
International Journal of Pattern Recognition and Artificial Intelligence, page 1940005, 2018.
<br>
</li>
<li>
Tensor Belief Propagation.
<br>
Andrew Wrigley, Wee Sun Lee, and Nan Ye.
<br>
In Proceedings of the International Conference on Machine Learning, 2017.
</li>
<li>
<span class="paper">Modelling imperfect presence data obtained by citizen science. </span>
<br>
Kerrie Mengersen, Erin E. Peterson, Sam Clifford, Nan Ye, June Kim, Tomasz Bednarz, Ross Brown, Allan James, Julie Vercelloni, Alan R. Pearse, Jacqueline Davis, and Vanessa Hunter.
<br>
Environmetrics, 2017.
<br>
</li>
<li>
<span class="paper">DESPOT: Online POMDP Planning with Regularization.</span>
<br>
Nan Ye, Adhiraj Somani, David Hsu, and Wee Sun Lee.
<br>
Journal of Artificial Intelligence Research, 58:231–266, 2017.
<br>
</li>
<li>
<span class="paper">Optimization Methods for Inverse Problems.</span>
<br>
Nan Ye, Farbod Roosta-Khorasani, and Tiangang Cui.
<br>
In David R. Wood, Jan de Gier, Cheryl E. Praeger, and Terence Tao, editors, MATRIX Annals, volume 2. Springer, 2017
<br>
</li>
<li>
<span class="paper">Robustness of Bayesian Pool-based Active Learning Against Prior Misspecification.</span>
[<a class="pub" href=pub/cuong2016robustness.pdf>PDF</a>]
<br>
Nguyen Viet Cuong,
Nan Ye,
Wee Sun Lee.
<br>
AAAI 2016.
</li>
<li>
<span class="paper">Intention-Aware Online POMDP Planning for Autonomous Driving in a Crowd.</span>
[<a class="pub" href="pub/bai2015intention.pdf">PDF</a>]
<br>
Haoyu Bai,
Shaojun Cai,
Nan Ye,
David Hsu,
Wee Sun Lee.
<br>
ICRA 2015.
</li>
<li>
<span class="paper">Near-optimal Adaptive Pool-based Active Learning with General Loss.</span>
[<a class="pub" href="pub/cuong2014near.pdf">PDF</a>]
<br>
<b>Google Best Student Paper Award</b>
<br>
Nguyen Viet Cuong,
Wee Sun Lee,
Nan Ye.
<br>
UAI 2014.
</li>
<li>
<span class="paper">Conditional Random Field with High-order Dependencies for Sequence
Labeling and Segmentation</span>.
[<a class="pub" href=pub/cuong2014conditional.pdf>PDF</a>]
[<a href="code/HOSemiCRF.zip">Code</a>]
<br>
Nguyen Viet Cuong,
Nan Ye,
Wee Sun Lee,
Hai Leong Chieu.
<br>
JMLR 15 (Mar):981−1009, 2014.
</li>
<li>
<span class="paper">DESPOT: Online POMDP Planning with Regularization</span>.
[<a class="pub" href=pub/somani2013despot.pdf>PDF</a>]
[<a href=pub/somani2013despot-sup.pdf>Supplement</a>]
[<a href=http://bigbird.comp.nus.edu.sg/pmwiki/farm/appl/>Code</a>]
<br>
Adhiraj Somani,
Nan Ye,
David Hsu,
Wee Sun Lee.
<br>
NIPS 2013.
</li>
<li>
<span class="paper">Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion</span>.
[<a class="pub" href=pub/cuong2013active.pdf>PDF</a>]
<br>
Nguyen Viet Cuong,
Wee Sun Lee,
Nan Ye,
Kian Ming A. Chai,
and
Hai Leong Chieu.
<br>
NIPS 2013.
</li>
<li>
<span class="paper">Optimizing F-measures: A Tale of Two Approaches</span>.
[<a class="pub" href=pub/fscore-icml12/fscore.pdf>PDF</a>]
[<a href=pub/fscore-icml12/fscore-appendix.pdf>Supplement</a>]
[<a href=pub/fscore-icml12/fscore.zip>Code</a>]
<br>
Nan Ye,
Kian Ming A. Chai,
<a class="author" href="http://www.comp.nus.edu.sg/~leews">Wee Sun Lee</a>,
and
<a class="author" href="http://www.comp.nus.edu.sg/~g0404406">Hai Leong Chieu</a>.
<br>
ICML 2012.
</li>
<li>
<span class="paper">Semi-Markov Conditional Random Field with High-Order Features</span>.
[<a class="pub" href="pub/crf-icmlw11.pdf">PDF</a>]
[<a href="https://github.com/nvcuong/HOSemiCRF">Code</a>]
<br>
Viet Cuong Nguyen,
Nan Ye,
<a class="author" href="http://www.comp.nus.edu.sg/~leews">Wee Sun Lee</a>,
and
<a class="author" href="http://www.comp.nus.edu.sg/~g0404406">Hai Leong Chieu</a>.
<br>
ICML Workshop on Structured Sparsity: Learning and Inference, 2011.
</li>
<li>
<span class="paper">Learning from Streams</span>.
[<a class="pub" href="pub/stream-alt09.pdf">PDF</a>]
<br>
<a class="author" href="http://www.comp.nus.edu.sg/~sanjay">Sanjay Jain</a>,
<a class="author" href="http://www.comp.nus.edu.sg/~fstephan">Frank Stephan</a>,
and
Nan Ye.
<br>
ALT 2009: 338-352.
</li>
<li>
<span class="paper">Domain adaptive bootstrapping for named entity recognition</span>.
[<a class="pub" href="pub/adaptive-emnlp09.pdf">PDF</a>]
<br>
Dan Wu,
<a class="author" href="http://www.comp.nus.edu.sg/~leews">Wee Sun Lee</a>,
Nan Ye
and
<a class="author" href="http://www.comp.nus.edu.sg/~g0404406">Hai Leong Chieu</a>.
<br>
EMNLP 2009: 1523-1532.
</li>
<li>
<span class="paper">Conditional Random Fields with High-Order Features for Sequence Labeling</span>.
[<a class="pub" href="pub/crf-nips09.pdf">PDF</a>]
<br>
Nan Ye,
<a class="author" href="http://www.comp.nus.edu.sg/~leews">Wee Sun Lee</a>,
<a class="author" href="http://www.comp.nus.edu.sg/~g0404406">Hai Leong Chieu</a>
and
Dan Wu.
<br>
NIPS 2009: 2196-2204.
</li>
<li>
<span class="paper">Prescribed Learning of R.E. Classes</span>.
[<a class="pub" href="pub/represcribed-tcs09.pdf">PDF</a>]
<br>
<a class="author" href="http://www.comp.nus.edu.sg/~sanjay">Sanjay Jain</a>,
<a class="author" href="http://www.comp.nus.edu.sg/~fstephan">Frank Stephan</a>
and
Nan Ye.
<br>
Theoretical Compututer Science 410(19): 1796-1806 (2009).
</li>
<li>
<span class="paper">Prescribed Learning of Indexed Families</span>.
[<a class="pub" href="pub/prescribed-fi08.pdf">PDF</a>]<br>
<a class="author" href="http://www.comp.nus.edu.sg/~sanjay">Sanjay Jain</a>,
<a class="author" href="http://www.comp.nus.edu.sg/~fstephan">Frank Stephan</a>
and
Nan Ye.<br>
Fundamental Informatica 83(1-2): 159-175 (2008).<br>
</li>
<li>
<span class="paper">On Preprocessing and Antisymmetry in de novo Peptide Sequencing: Improving Efficiency and Accuracy</span>.
<br>
<a class="author" href="http://sourcedb.cas.cn/sourcedb_qibebt_cas/yw/zjrc/201008/t20100818_2925860.html">Kang Ning</a>,
Nan Ye
and
<a class="author" href="http://www.comp.nus.edu.sg/~leonghw">Hon Wai Leong</a>.
<br>
Journal of Bioinformatics and Computational Biology 6(3): 467-492 (2008).
</li>
<li>
<span class="paper">Prescribed Learning of R.E. Classes</span>.
[<a class="pub" href="pub/represcribed-alt07.pdf">PDF</a>]
<br>
<a class="author" href="http://www.comp.nus.edu.sg/~sanjay">Sanjay Jain</a>,
<a class="author" href="http://www.comp.nus.edu.sg/~fstephan">Frank Stephan</a>
and
Nan Ye.
<br>
ALT 2007: 64-78.
</li>
</ul>
</div> <!--end of research-->
<div class="sectioncontent" id="teaching">
<h3 class=sectiontitle>Teaching</h3>
<ul>
<li>
2024 1-5 Jul.
<span class="course">
<a href="teach/amsiws2024/index.html">AMSI Winter School. Reinforcement Learning</a>
</span>
</li>
<li>
2022 Semester 2.
<span class="course">
<a href="teach/data7703/index.html">DATA7703 Machine Learning for Data Scientists.</a>
</span>
</li>
<li>
2022 Semester 1.
<span class="course">
<a href="teach/stat3007/index.html">STAT3007/7007 Deep Learning.</a>
</span>
</li>
<li>
2022 Semester 1.
<span class="course">
STAT2201 Analysis of Engineering & Scientific Data.
</span>
</li>
<li>
2021 Semester 2.
<span class="course">
STAT2201 Analysis of Engineering & Scientific Data.
</span>
</li>
<li>
2021 Semester 2.
<span class="course">
DATA7703 Machine Learning for Data Scientists.
</span>
</li>
<li>
2021 Semester 1.
<span class="course">
STAT3007/7007 Deep Learning.
</span>
</li>
<li>
2020 Semester 2.
<span class="course">
DATA7703 Machine Learning for Data Scientists.
</span>
</li>
<li>
2020 Semester 2.
<span class="course">
STAT4402/7503 Advanced Statistics II (Deep Learning).
</span>
</li>
<li>
2020 Semester 1.
<span class="course">
DATA7001 Introduction to Data Science.
</span>
</li>
<li>
2019 Semester 2.
<span class="course">
<a href="teach/stat4402/index.html">STAT4402/7503 Advanced Statistics II (Deep Learning).</a>
</span>
</li>
<li>
2019 Semester 2.
<span class="course">
STAT3500/7500 Problems & Applications in Modern Statistics.
</span>
</li>
<li>
2019 Semester 2.
<span class="course">
DATA7001 Introduction to Data Science.
</span>
</li>
<li>
2019 Semester 1.
<span class="course">
DATA7001 Introduction to Data Science.
</span>
</li>
<li>
2018 Semester 2.
<span class="course">
<a href="teach/stat3500/index.html">STAT3500/7500 Problems & Applications in Modern Statistics.</a>
</span>
</li>
<li>
2015 Semester 1.
<span class="course">MXB361 Aspects of Computational Science.</span>
</li>
</div>
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