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<html>
<head>
<title>Research</title>
</head>
<body background="images/crysback.jpg" bgcolor="white" lang="EN-US" link="blue" vlink="blue">
<center>
<table border="0">
<tbody><tr>
<th align="center">
<p> <font face="Book Antiqua" size=3 color="brown">
<b> Search, Search, and Research. <br>
On this exploration Odyssey, silence is golden.<br>
Learning comes from errors. <br></b></font>
</p>
</th>
<td align="center">
<image src="images/mountain.jpg" height="100">
</td>
</tr>
</tbody>
</table>
<img src="images/strings.gif" width="550"> <br>
</center>
<p><font face="Arial, Helvetica, sans-serif"><b><font color="#660099", size=3>Research interests</font></b></font>
<blockquote>
My most recent interests are focusing on mathematics for data sciences, in particular topological and geometric methods for high dimensional data analysis and statistical machine learning, with applications in computational biology and information technology.
</blockquote>
<hr>
<p><font face="Arial, Helvetica, sans-serif"><b><font color="#660099", size=3>
Monograph</font></b></font>
<blockquote>
<a href="https://github.com/yao-lab/publication/blob/master/Thesis_YaoY_Berkeley.pdf">A Dynamic Theory of Learning</a>.
PhD Dissertation, University of Calfornia at Berkeley. Supervisor: Steve Smale. December, 2006.
<br>
Published as <i> A Dynamic Theory of Learning -- Online Learning and Stochastic Algorithms in Reproducing Kernel Hilbert Spaces</i>, <a href="http://www.vdm-publishing.com/">Verlag Dr. Muller</a>, ISBN: 978-3-639-09390-2. 2008.
</font>
<br>
</blockquote>
<blockquote>
<a href="https://yao-lab.github.io/book_datasci/">A Mathematical Introduction to Data Analysis</a>.
preprint.
</font>
<br>
</blockquote>
<hr>
<p><font face="Arial, Helvetica, sans-serif"><b><font color="#660099">
Papers and Preprints</font></b></font>
<UL>
<font size=2>
<li>
<B>
Who Likes What? – SplitLBI in Exploring Preferential Diversity of Ratings.
</B>
<br>
Qianqian Xu, Jiechao Xiong, Zhiyong Yang, Xiaochun Cao, Qingming Huang and Yuan Yao.
<br>
<I> AAAI Conference on Artificial Intelligence (AAAI) </I>, New York, Feb 7-12, 2020.
<br>
[<a href="https://github.com/qianqianxu010/AAAI2020"> code </a>]
<p>
</li>
<li>
<B>
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.
</B>
<br>
Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou.
<br>
<I> AAAI Conference on Artificial Intelligence (AAAI) </I>, New York, Feb 7-12, 2020.
<br>
[<a href="https://arxiv.org/abs/1910.02249"> arXiv:1910.02249 </a>]
<p>
</li>
<li>
<B>
iSplit LBI: Individualized Partial Ranking with Ties via Split LBI.
</B>
<br>
Qianqian Xu, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang and Yuan Yao.
<br>
<I> Annual Conference on Neural Information Processing Systems (NeurIPS)</I>, Vancuver, Canada, 3896–3906, 2019.
<br>
[<a href="https://github.com/yao-lab/NeurIPS2019-iSplitLBI/blob/master/poster/NeurIPS2019-iSplitLBI.pdf"> pdf </a>][<a href="https://github.com/yao-lab/NeurIPS2019-iSplitLBI"> code </a>][<a href="https://github.com/yao-lab/NeurIPS2019-iSplitLBI/blob/master/poster/NeurIPS2019-iSplitLBI-Poster.pdf"> poster </a>]
<p>
</li>
<li>
<B>
Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size.
</B>
<br>
Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu and Yuan Yao.
<br>
<I>IEEE Transactions on Knowledge and Data Engineering (TKDE)</I>, 2020 (Early Access). Extended from AAAI'18 version.
<br>
[<a href="https://ieeexplore.ieee.org/document/8918070"> 10.1109/TKDE.2019.2956700 </a>]
<p>
</li>
<li>
<B>
Parsimonious Deep Learning: A Differential Inclusion Approach with Global Convergence.
</B>
<br>
Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, and Yuan Yao.
<br>
[<a href="https://arxiv.org/abs/1905.09449"> arXiv:1905.09449 </a>][<a href="https://github.com/yao-lab/FSplitLBI"> GitHub source </a>]
<p>
</li>
<li>
<B>
$S^2$-LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning.
</B>
<br>
Yanwei Fu, Donghao Li, Xinwei Sun, Shun Zhang, Yizhou Wang, and Yuan Yao.
<br>
[<a href="https://arxiv.org/abs/1904.10873"> arXiv:1904.10873 </a>]
<p>
</li>
<li>
<B>
Deep Robust Subjective Visual Property Prediction in Crowdsourcing.
</B>
<br>
Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang, Yuan Yao.
<br>
<I> Conference on Computer Vision and Pattern Recognition (CVPR)</I>, Long Beach, CA, June 16-20, 2019
<br>
[<a href="https://arxiv.org/abs/1903.03956"> arXiv:1903.03956 </a>][<a href="https://github.com/qianqianxu010/CVPR19-Deep-Robust-Subjective-Visual-Property-Prediction-in-Crowdsourcing"> GitHub source </a>]
<p>
</li>
<li>
<B>
Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective.
</B>
<br>
Chao Gao, Yuan Yao, Weizhi Zhu.
<br>
[<a href="https://arxiv.org/abs/1903.01944"> arXiv:1903.01944 </a>][<a href="https://github.com/zhuwzh/Robust-GAN-Scatter"> Github Source </a>]
<p>
</li>
<li>
<B>
A Convergence Analysis of Nonlinearly Constrained ADMM in Deep Learning.
</B>
<br>
Jinshan Zeng, Shao-Bo Lin, Yuan Yao.
<br>
[<a href="https://arxiv.org/abs/1902.02060"> arXiv:1902.02060 </a>]
<p>
</li>
<li>
<B>
Zero-Shot Learning via Recurrent Knowledge Transfer.
</B>
<br>
Bo Zhao, Xinwei Sun, Xiaopeng Hong, Yuan Yao, and Yizhou Wang.
<br>
2019 IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa Village, HI, USA, 7-11 Jan. 2019.
<br>
[<a href="https://doi.org/10.1109/WACV.2019.00144"> DOI: 10.1109/WACV.2019.00144 </a>] [<a href="https://github.com/yao-lab/Zero-shot-Learning-via-Recurrent-Knowledge-Transfer"> GitHub source </a>]
<p>
</li>
<li>
<B>
On Breiman's Dilemma in Neural Networks: Phase Transitions of Margin Dynamics.
</B>
<br>
Weizhi Zhu, Yifei Huang, Yuan Yao.
<br>
[<a href="https://arxiv.org/abs/1810.03389"> arXiv:1810.03389 </a>]
<p>
</li>
<li>
<B>
Robust Estimation and Generative Adversarial Networks.
</B>
<br>
Chao Gao, Jiyi Liu, Yuan Yao, Weizhi Zhu.
<br>
<I>International Conference on Learning Representations (ICLR)</I>, New Orleans, Louisiana, United States, May 6 - May 9, 2019.
<br>
[<a href="https://arxiv.org/abs/1810.02030"> arXiv:1810.02030 </a>][<a href="https://openreview.net/forum?id=BJgRDjR9tQ"> ICLR'19 </a>][<a href="https://github.com/zhuwzh/Robust-GAN-Center"> GitHub source </a>]
<p>
</li>
<li>
<B>
Data-Driven Tight Frame for Cryo-EM Image Denoising and Conformational Classification.
</B>
<br>
Yin Xian, Hanlin Gu, Wei Wang, Xuhui Huang, Yuan Yao, Yang Wang, Jian-Feng Cai.
<br>
<I>The 6th IEEE Global Conference on Signal and Information Processing</I>, Anaheim, California, Nov 26-29, 2018.
<br>
[<a href="https://arxiv.org/abs/1810.08829"> arXiv:1810.08829 </a>] [<a href="https://github.com/poline3939/Cryo-EM-Denoising"> GitHub source </a>]
<p>
</li>
<li>
<B>
A Margin-based MLE for Crowdsourced Partial Ranking.
</B>
<br>
Qianqian Xu, Jiechao Xiong, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, Yuan Yao.
<br>
<I>In 2018 ACM Multimedia Conference (MM’18), October 22–26, 2018, Seoul, Republic of Korea. ACM, New York, NY, USA.</I>
<br>
[<a href="https://arxiv.org/abs/1807.11014"> arXiv:1807.11014 </a>]
<p>
</li>
<li>
<B>
FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis
</B>
<br>
Xinwei Sun, Lingjing Hu, Fandong Zhang, Yuan Yao, Yizhou Wang
<br>
<I>The 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain, 2018</I>
<br>
[<a href="https://arxiv.org/abs/1807.08125"> arXiv:807.08125 </a>]
<p>
</li>
<li>
<B>
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
</B>
<br>
Bo Zhao, Xinwei Sun, Yanwei Fu, Yuan Yao, Yizhou Wang
<br>
<I>The 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018</I>
<br>
[<a href="https://arxiv.org/abs/1806.04360"> arXiv:1806.04360 </a>] [<a href="http://proceedings.mlr.press/v80/zhao18c.html"> link </a>][<a href="https://github.com/yao-lab/MSplitLBI"> GitHub source1 </a>][<a href="https://github.com/PatrickZH/MSplitLBI"> GitHub source2</a>]
<p>
<li>
<B>
From Social to Individuals: a Parsimonious Path of Multi-level Models for Crowdsourced Preference Aggregation
</B>
<br>
Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang, Yuan Yao
<br>
<I>IEEE Transactions on Pattern Analysis and Machine Intelligence</I>, 41(4):844-856, 2019. Extended from MM'16 in [<a href="https://arxiv.org/abs/1607.03401"> arXiv:1607.03401 </a>].
<br>
[<a href="https://arxiv.org/abs/1804.11177"> arXiv:1804.11177 </a>] [<a href="https://ieeexplore.ieee.org/document/8319957/"> doi: 10.1109/TPAMI.2018.2817205 </a>][<a href="https://github.com/yao-lab/TPAMI2018"> GitHub source</a>]
<p>
<li>
<B>
A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training
</B>
<br>
Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao
<br>
<I>The 6th International Conference on Learning Representations (ICLR 2018), Workshop Track</I>
<br>
[<a href="https://arxiv.org/abs/1803.09082"> arXiv:1803.09082 </a>]
<p>
<li>
<B>
Global Convergence of Block Coordinate Descent in Deep Learning
</B>
<br>
Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao
<br>
[<a href="https://arxiv.org/abs/1803.00225"> arXiv:1803.00225 </a>]
<p>
</li>
<li>
<B>
Finding Global Optima in Nonconvex Stochastic Semidefinite Optimization with Variance Reduction
</B>
<br>
Jinshan Zeng, Ke Ma, Yuan Yao
<br>
Proceedings of the 21st International Conference on Artificial Intelligence and Statistics <I>(AISTATS)</I>, Lanzarote, Spain, 2018.
<br>
[<a href="https://arxiv.org/abs/1802.06232"> arXiv:1802.06232 </a>] [<a href="http://proceedings.mlr.press/v84/zeng18a/zeng18a.pdf"> link </a>]
<p>
</li>
<li>
<B>
A Unified Dynamic Approach to Sparse Model Selection.
</B>
<br>
Chendi Huang, Yuan Yao.
<br>
Proceedings of the 21st International Conference on Artificial Intelligence and Statistics <I>(AISTATS)</I>, Lanzarote, Spain, 2018.
<br>
[<a href="https://arxiv.org/abs/1810.03608"> arXiv:1810.03608 </a>] [<a href="http://proceedings.mlr.press/v84/huang18a/huang18a.pdf"> link </a>]
<p>
</li>
<li>
<B>
Stochastic Non-Convex Ordinal Embedding with Stabilized Barzilai-Borwein Step Size
</B>
<br>
Ke Ma, Jinshan ZENG, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan Yao
<br>
<I> The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)</I>, New Orleans, Louisiana, Feb 2-7, 2018.
<br>
[<a href="https://arxiv.org/abs/1711.06446"> arXiv:1711.06446 </a>] [<a href="https://github.com/alphaprime/Stabilized_Stochastic_BB"> GitHub Source in Matlab </a>]
<p>
</li>
<li>
<B>
HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation
</B>
<br>
Qianqian Xu, Jiechao Xiong, Xi Chen, Qingming Huang, Yuan Yao
<br>
<I> The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)</I>, New Orleans, Louisiana, Feb 2-7, 2018.
<br>
[<a href="https://arxiv.org/abs/1711.05957"> arXiv:1711.05957 </a>] [<a href="https://github.com/yuany-pku/activesample"> GitHub </a>]
<p>
</li>
<li>
<B>
Accelerated Block Coordinate Proximal Gradients with Applications in High Dimensional Statistics
</B>
<br>
Tsz Kit Lau and Yuan Yao
<br>
<I>The 10th NIPS Workshop on Optimization for Machine Learning (NIPS 2017)</I>, Long Beach, California, Dec 3-8, 2017.
<br>
[<a href="https://arxiv.org/abs/1710.05338"> arXiv:1710.05338 </a>]
<p>
</li>
<li>
<B>
Exploring Outliers in Crowdsourced Ranking for QoE
</B>
<br>
Qianqian Xu, Ming Yan, Chendi Huang, Jiechao Xiong, Qingming Huang, and Yuan Yao
<br>
<I> ACM Multimedia 2017 (Oral presentation)</I>, Mountain View, California, Oct 23-27, 2017.
<br>
[<a href="https://arxiv.org/abs/1707.07539"> arXiv:1707.07539 </a>]
<p>
</li>
<li>
<B>
GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction
</B>
<br>
Xinwei Sun, Lingjing Hu, Yuan Yao, and Yizhou Wang
<br>
<I> Medical Image Computing and Computer Assisted Interventions Conference (MICCAI)</I>, Quebec City, Canada, Sept 10-14, 2017.
<br>
[<a href="https://arxiv.org/abs/1705.09249"> arXiv:1705.09249 </a>]
<p>
</li>
<li>
<B>
Boosting with Structural Sparsity: A Differential Inclusion Approach
</B>
<br>
Chendi Huang, Xinwei Sun, Jiechao Xiong, and Yuan Yao
<br>
<I>Applied and Computational Harmonic Analysis</I>, preprint, 8 February 2018.
<br>
[<a href="https://arxiv.org/abs/1704.04833"> arXiv:1704.04833 </a>] [<a href="https://doi.org/10.1016/j.acha.2017.12.004"> https://doi.org/10.1016/j.acha.2017.12.004 </a>]
<p>
</li>
<li>
<B>
A Statistical Learning Approach for Drug Sensitivity Prediction with Cancer Cell Line Data
</B>
<br>
Lijing Wang, Yangzhong Tang, Stevan Djakovic, Julie Rice, Tony Wu, Daniel J. Anderson, and Yuan Yao
<br>
<I><a href="http://dahshu.org/events/cph2017/index.html"> Dahshu 2017: Data Science and Computational Precision Health</a> </I>, San Francisco, Feb 20-22, 2017.
<br>
[<a href="http://math.stanford.edu/~yuany/publications/poster_CleaveBioCPH2017_ForReview.pdf"> Poster </a>]
<p>
<li>
<B>
Split LBI: An Iterative Regularization Path with Structural Sparsity
</B>
<br>
Chendi Huang, Xinwei Sun, Jiechao Xiong, Yuan Yao
<br>
<I>Advances in Neural Information Processing Systems 29 (NIPS 2016)</I>, Barcelona, Spain, December 5-10, 2016.
<br>
[<a href="https://papers.nips.cc/paper/6288-split-lbi-an-iterative-regularization-path-with-structural-sparsity"> NIPS link </a>] [ <a href="https://github.com/yuany-pku/split-lbi"> Matlab codes at GitHub </a>]
<p>
<li>
<B>
Learning rates of regression with q-norm loss and threshold
</B>
<br>
Ting Hu, Yuan Yao
<br>
<I>Analysis and Applications</I>, Volume 14, Issue 06, November 2016.
<br>
[<a href="http://dx.doi.org/10.1142/S0219530516400030"> DOI </a>]
<p>
<li>
<B>
Parsimonious Mixed-Effects HodgeRank for Crowdsourced Preference Aggregation
</B>
<br>
Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan Yao
<br>
<I>ACM Multimedia Conference (ACMMM)</I>, Amsterdam, Netherlands, October 15-19, 2016.
<br>
[<a href="http://arxiv.org/abs/1607.03401"> arXiv:1607.03401 </a>] [<a href="http://math.stanford.edu/~yuany/publications/AMM-20160712.pdf"> pdf </a>]
<p>
<li>
<B>
False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking
</B>
<br>
Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan Yao
<br>
<I>Proceedings of The 33rd International Conference on Machine Learning (ICML)</I>, New York, June 19-24, 2016.
<br>
[<a href="http://arxiv.org/abs/1605.05860"> arXiv:1605.05860 </a>] [<a href="http://math.stanford.edu/~yuany/publications/ICML2016_cameraready_ID_600.pdf"> pdf </a>] [<a href="http://math.stanford.edu/~yuany/publications/ICML2016_camerareadySI_ID_600.pdf"> supplementary </a>]
<p>
<li>
<B>A Tutorial on Libra: R package for the Linearized Bregman Algorithm in high dimensional statistics
</B>
<br>
Jiechao Xiong, Feng Ruan, and Yuan Yao
<br>
<I>Handbook of Big Data Analytics</I>, Ed. by H\"{a}rdle, Lu and Shen, Springer, 2018
<br>
[<a href="http://math.stanford.edu/~yuany/course/reference/Libra_Tutorial_springer.pdf"> PDF in Chinese </a>] [<a href="http://math.stanford.edu/~yuany/course/reference/BigData_004_final_v8.pdf"> PDF in English </a>] [<a href="http://arxiv.org/abs/1604.05910"> arXiv </a>] [<a href="https://cran.r-project.org/web/packages/Libra/index.html"> Cran R website </a>]
[<a href="https://doi.org/10.1007/978-3-319-18284-1"> DOI: https://doi.org/10.1007/978-3-319-18284-1 </a>]
<p>
<li>
<B>Mixed and missing data: a unified treatment with latent graphical models
</B>
<br>
Xiao Li, Jinzhu Jia, and Yuan Yao
<br>
[<a href="http://arxiv.org/abs/1511.04656"> arXiv:1511.04656 </a>]
<p>
<li>
<B>Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications
</B>
<br>
Qing Wang, Hengshu Zhu, Wei Hu, Zhiyong Shen, and Yuan Yao
<br>
<I>ACM SIGKDD</I>, Sydney, Australia, August 10-13, 2015.
<br>
[<a href="publications/kdd_t3m.pdf"> pdf </a>] [<a href="http://bdl.baidu.com/soccer/tacpat.html"> Demo @Baidu-BDL</a>]
<p>
<li>
<B>Analysis of Crowdsourced Sampling Strategies for HodgeRank with Sparse Random Graphs
</B>
<br>
Braxton Osting, Jiechao Xiong, Qianqian Xu, and Yuan Yao
<br>
<I>Applied and Computational Harmonic Analysis</I>, 41 (2): 540-560, 2016
<br>
[<a href="http://arxiv.org/abs/1503.00164"> arXiv:1503.00164 </a>] [<a href="http://authors.elsevier.com/sd/article/S1063520316000300
"> ACHA online </a>] [<a href="data/TIP_matlab.zip">Matlab codes to reproduce our results</a>]
<p>
<li>
<B>Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels
</B>
<br>
Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Jiechao Xiong, Shaogang Gong, Yizhou Wang, and Yuan Yao
<br>
<I>IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)</I>, vol.38, no.3, pp. 563-577, March 2016.
<br>
[<a href="http://arxiv.org/abs/1501.06202"> arXiv:1501.06202 </a>] [<a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2015.2456887"> doi:10.1109/TPAMI.2015.2456887 </a>]
<p>
<li>
<B>Robust Statistical Ranking: Theory and Algorithms
</B>
<br>
Qianqian Xu, Jiechao Xiong, Qingming Huang and Yuan Yao
<br>
[<a href="publications/robustranking.pdf">pdf</a>] [<a href="http://arxiv.org/abs/1408.3467"> arXiv:1408.3467 </a>]
<p>
<li>
<B>Fast Adaptive Least Trimmed Squares for Robust Evaluation of Quality of Experience.
</B>
<br>
Qianqian Xu, <a href="http://www.math.ucla.edu/~yanm/">Ming Yan</a>, and Yuan Yao
<br>
[<a href="http://arxiv.org/abs/1407.7636"> arXiv:1407.7636 </a>] [<a href="https://code.google.com/p/irls/">Matlab in Google code</a>]
<p>
<li>
<B>Geometric Tight Frame based Stylometry for Art Authentication of van Gogh Paintings
</B>
<br>
Haixia Liu, Raymond H. Chan, and Yuan Yao
<br>
<I>Applied and Computational Harmonic Analysis</I>, 41(2): 590-602, 2016
<br>
[<a href="publications/vangogh.pdf">pdf</a>] [<a href="http://arxiv.org/abs/1407.0439">arXiv:1407.0439</a>] [<a href="http://www.sciencedirect.com/science/article/pii/S1063520315001566"> ACHA online Dec 2, 2015 </a>]
<p>
<li>
<B>Sparse Recovery via Differential Inclusions
</B>
<br>
<a href="www.math.ucla.edu/~sjo">Stanley Osher</a>, Feng Ruan, Jiechao Xiong, Yuan Yao and <a href="www.math.ucla.edu/~wotaoyin">Wotao Yin</a>
<br>
<I>Applied and Computational Harmonic Analysis</I>, 41(2):436-469, 2016
<br>
[<a href="publications/bregman.pdf">pdf</a>] [<a href="http://arxiv.org/abs/1406.7728"> arXiv:1406.7728 </a>] [<a href="http://dx.doi.org/10.1016/j.acha.2016.01.002"> ACHA online January 14, 2016 </a>] [<a href="https://cran.r-project.org/web/packages/Libra/index.html"> R package: Libra </a>]
<p>
<li>
<B>Interestingness Prediction by Robust Learning to Rank.
</B>
<br>
Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong, and Yuan Yao
<br>
13th European Conference on Computer Vision (ECCV), Zurich, Switzerland, Sep 8-12, 2014.
<br>
[<a href="publications/eccv2014.pdf">pdf</a>]
<p>
<li>
<B> Online Learning as Stochastic Approximations of Regularization Paths: Optimality and Almost-sure Convergence.</B>
<br><a href="http://people.maths.ox.ac.uk/~tarres/">Pierre Tarres</a> and Yuan Yao.
<br> <i> IEEE Transactions on Information Theory </i>, 60(9):5716-5735, 2014.
<br> short report appeared in <i>Mathematisches Forschungsinstitut Oberwolfach, Report 30/2008, Learning Theory and Approximation</i>.
<br>
[<a href="publications/TarresYao.IEEEIT14.pdf">pdf</a>] [<a href="abs_OWR.pdf">Oberwolfach Report</a>][<a href="http://arxiv.org/abs/1103.5538">arXiv.org:1103.5538</a>]
<p>
<li>
<B>Online HodgeRank on Random Graphs for Crowdsourceable QoE Evaluation.
</B>
<br>
Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao
<br>
<I>IEEE Transactions on Multimedia</I>, 16(2):373-386, Feb. 2014.
<br>
[<a href="publications/TMM13.pdf">pdf</a>]
<p>
<li>
<B>Robust Evaluation for Quality of Experience in Crowdsourcing.
</B>
<br>
Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao
<br>
<a href="http://www.acmmm13.org/"> <I>ACM Multimedia 2013</I>.</a>
<br>
[<a href="publications/ACMMM13.pdf">pdf</a>]
<p>
<li>
<B>Hierarchical Nystrom Methods for Constructing Markov State Models for Conformational Dynamics.
</B>
<br>
Yuan Yao, Raymond Z. Cui, Gregory R. Bowman, Daniel Silva, Jian Sun, Xuhui Huang
<br>
<I>The Journal of chemical physics</I> 2013 May 7, 138 (17):174106. <a href="http://arxiv.org/abs/1301.0974">arXiv:1301.0974, </a> 2013
<p>
<li>
<B>The Landscape of Complex Networks: Critical Nodes and A Hierarchical Decomposition.</B>
<br>
Weinan E, Jianfeng Lu, and Yuan Yao.
<br>
<I>Methods and Applications of Analysis</I>, special issue in honor of Professor Stanley Osher on his 70th birthday, 20(4):383-404, 2013.
<br>[<a href="publications/ELY.MAA13.pdf"> pdf </a>] [<a href="http://arxiv.org/abs/1204.6376">arXiv:1204.6376</a>]
<p>
<li>
<B>Online Crowdsourcing Subjective Image Quality Assessment.</B>
<br>
Qianqian Xu, Qingming Huang, and Yuan Yao.
<br>
<a href="http://www.acmmm12.org/">ACM Multimedia 2012.</a>
<br>
[<a href="publications/ACMMM12.pdf">pdf</a>]
<p>
<li>
<B>HodgeRank on Random Graphs for Subjective Video Quality Assessment.</B>
<br>
Qianqian Xu, Qingming Huang, Tingting Jiang, Bowei Yan, Weisi Lin, and Yuan Yao.
<br>
<a href=""> </a> IEEE Transactions on Multimedia, 14(3):844-857, 2012
<br>
[<a href="publications/TMM12-final.pdf">pdf</a>][<a href="publications/BatchHodge.zip"> Matlab codes in zip </a>]
<p>
<li>
<B>Compressive Network Analysis.</B>
<br>
Xiaoye Jiang, Yuan Yao, Han Liu, and Leo Guibas
<br>
<I>IEEE Transactions on Automatic Control</I>, 59(16): preprint, 2014
<br>
On the <a href="http://arxiv.org/abs/1104.4605"> arXiv:1104.4605, </a> 2011
<p>
<li>
<B>Detecting Network Cliques with Radon Basis Pursuit.</B>
<br>
Xiaoye Jiang, Yuan Yao, Han Liu, and Leo Guibas
<br>
<a href="http://www.aistats.org/">AISTATS 2012.</a>
<br>
[<a href="publications/aistats12.pdf">pdf</a>]
<p>
<li>
<B>Random Partial Paired Comparison for Subjective Video Quality Assessment via HodgeRank.</B>
<br>
Qianqian Xu, Tingting Jiang, Yuan Yao, Qingming Huang, Bowei Yan, Weisi Lin.
<br>
<a href="http://www.acmmm11.org/">ACM Multimedia 2011.</a>
<br>
[<a href="publications/ACM_MM_2011_preprint_mfp12x.pdf">pdf</a>]
<p>
<li>
<B>Simulating Human Saccadic Scanpaths on Natural Images.</B>
<br>
Wei Wang, Cheng Chen, Yizhou Wang, Tingting Jiang, Fang Fang, Yuan Yao.
<br>
<a href="http://www.cvpr2011.org/">IEEE Computer Vision and Pattern Recognition (<it>CVPR</it>) 2011.</a>
<br>
[<a href="publications/cvpr2011.pdf">pdf</a>]
<p>
<li>
<B>Overcomplete Radon Bases for Target Property Management in Sensor Networks.</B>
<br>
<a href="http://graphics.stanford.edu/projects/lgl/person.php?id=xiaoyej">Xiaoye Jiang</a>, Mo Li, Yuan Yao, and <a href="http://www-graphics.stanford.edu/~guibas/ ">Leonidas Guibas</a>.
<br>
<a href="http://ipsn.acm.org/2011/">The 10th International Conference on Information Processing in Sensor Networks, Chicago, </i>(ACM IPSN) 2011.</i></a>
<br>
[<a href="publications/ipsn2011.pdf">pdf</a>]
<p>
<li>
<B>Hodge Decomposition of Paired Comparison Flows in Click-through Data.</B>
<br>
Zhanglong Ji, Yang An, Ying Chen, Yuan Yao, Jun Xu, and Hang Li.
<br>
Tech Report, appeared in <a href="http://limu.ait.kyushu-u.ac.jp/MPR2010/">The 6th Joint Workshop on Machine Perception and Robotics (MPR)</i>, Fukuoka, Japan, 2010.</i></a>
<br>
[<a href="publications/MPR2010.pdf">pdf</a>]
<p>
<li>
<B>Statistical Ranking and Combinatorial Hodge Theory.</B>
<br>
<a href="http://graphics.stanford.edu/projects/lgl/person.php?id=xiaoyej">Xiaoye Jiang</a>, <a href="http://math.berkeley.edu/~lekheng/">Lek-Heng Lim</a>, Yuan Yao and <a href="http://www.stanford.edu/~yyye/">Yinyu Ye</a>.
<br>
<i>Mathematical Programming</i>, Volume 127, Number 1, Pages 203-244, 2011.
<br>
[<a href="abs_hodge.html">Abstract</a>][<a href="publications/HodgeRank.MathProg.B.2010.pdf">pdf</a>][<a href=" http://arxiv.org/abs/0811.1067"> arxiv.org/abs/0811.1067</a>][<a href=" publications/MathProg.zip"> Matlab Codes</a>]
<p>
<li>
<B>On Complexity Issues of Online Learning Algorithms.</B>
<br>
Yuan Yao.
<br>
<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5625646&tag=1"> <i>IEEE Transactions on Information Theory</i></a>, 56(12): 6470 - 6481, 2010.
<br>
[<a href="publications/IT-complexity.pdf">pdf</a>]
<p>
<li>
<B> Constructing Multi-Resolution Markov State Models (MSMS) to Elucidate RNA Hairpin Folding Mechanisms.</B>
<br>
Huang, X., Y. Yao, J. Sun, L. Guibas, G. Carlsson and V.S. Pande.
<br>
<I>Proceedings of the Pacific Symposium on Biocomputing, 15, 228-239, (2010)</I>
<br>
[<a href="http://psb.stanford.edu/psb-online/proceedings/psb10/huang.pdf">pdf online</a>]
<p>
<li>
<B>Stable Identification of Cliques with Radon Basis Pursuit.</B>
<br>
<a href="http://graphics.stanford.edu/projects/lgl/person.php?id=xiaoyej">Xiaoye Jiang</a>, Yuan Yao, and <a href="http://www-graphics.stanford.edu/~guibas/ ">Leonidas Guibas</a>.
<br>
<I>preprint.</I>
<br>
[<a href="publications/RadonPursuit.pdf">pdf</a>]
<p>
<li>
<B>A Fast Geometric Clustering Method on Conformation Space of Biomolecules.</B>
<br>
<a href="http://www.stanford.edu/~sunjian/">Jian Sun</a>, Yuan Yao, <a href="http://csb.stanford.edu/~xhuang/">Xuhui Huang</a>, <a href="http://folding.stanford.edu/Pande/Main">Vijay Pande</a>, <a href="http://math.stanford.edu/~gunnar/">Gunnar Carlsson</a>, and <a href="http://www-graphics.stanford.edu/~guibas/ ">Leonidas Guibas</a>.
<br>
<I>preprint.</I>
<br>
[<a href="publications/kcenter_v9.pdf">pdf</a>]
<p>
<li>
<B>Topological Methods for Exploring Low-density States in Biomolecular Folding Pathways.</B>
<br>
Yuan Yao, Jian Sun, Xuhui Huang, Gregory Bowman, Gurjeet Singh, Michael Lesnick, <a href="http://folding.stanford.edu/Pande/Main">Vijay Pande</a>, <a href="http://www-graphics.stanford.edu/~guibas/ ">Leonidas Guibas</a> and <a href="http://math.stanford.edu/~gunnar/">Gunnar Carlsson</a>.
<br>
<i>J. Chem. Phys</i>. <B>130</B>, 144115 (2009).
<br>
[<a href="publications/RNA_mapper_JCP2009.pdf">pdf</a>][<a href="http://link.aip.org/link/?JCP/130/144115">Online Publication</a>][<a href="https://simtk.org/home/rna-mapper">SimTK Link: Data and Matlab Codes</a>] [Selected by <a href="http://www.vjbio.org/">Virtual Journal of Biological Physics Research, 04/15/2009</a>].
<p>
<li>
<B>Metric Learning for Phylogenetic Invariants.</B>
<br>
<a href="http://www.stat.uchicago.edu/~eriksson/">Eriksson, Nick</a> and Yuan Yao.
<br>
<i>preprint</i>.
<br>
[<a href="http://arxiv.org/abs/q-bio/0703034">arxiv.org/abs/q-bio/0703034</a>].
<p>
<li>
<B>Structural insight into RNA hairpin folding intermediates.</B>
<br>
Bowman, Gregory R., <a href="http://csb.stanford.edu/~xhuang/">Xuhui Huang</a>, Yuan Yao, <a href="http://www.stanford.edu/~sunjian/">Jian Sun</a>, <a href="http://math.stanford.edu/~gunnar/">Gunnar Carlsson</a>, <a href="http://www-graphics.stanford.edu/~guibas/ ">Leonidas Guibas</a> and <a href="http://folding.stanford.edu/Pande/Main">Vijay Pande</a>.
<br>
<i>Journal of American Chemistry Society</i>, 2008, 130 (30): 9676-9678.
<br>
[<a href="http://pubs.acs.org/cgi-bin/abstract.cgi/jacsat/2008/130/i30/abs/ja8032857.html">link</a>]
<p>
<li>
<B>On Early Stopping in Gradient Descent Learning.</B>
<br>
Yuan Yao, <a href="http://www.disi.unige.it/person/RosascoL/">Lorenzo Rosasco</a> and <a href="http://www.pascal-network.org/Network/Researchers/150/">Andrea Caponnetto</a>.
<br>
<a href="http://atlas.math.vanderbilt.edu/~ca/"><i>Constructive Approximation</i></a>, 2007, 26 (2): 289-315.
<br>
[<a href="publications/earlystop.pdf">pdf</a>]
<p>
<li>
<B>Adaptation for Regularization Operators in Learning Theory</B>
<br>
<a href="http://www6.cityu.edu.hk/ma/people/caponnetto.html">Andrea Caponnetto</a> and Yuan Yao.
<br>
<i>CBCL Paper \#265/AI Technical Report \#063, Massachusetts Institute of Technology,</i> Cambridge, MA, September, 2006.
<br>
<i> Analysis and Applications </i> vol. 08, no. 02, 2010
<br>
[<a href="publications/adapt_090319.pdf">pdf</a>][<a href="http://cbcl.mit.edu/projects/cbcl/publications/ps/MIT-CSAIL-TR-2006-063.pdf">pdf Tech-Report</a>]
<p>
<li>
<B>Mercer's Theorem, Feature Maps, and Smoothness</B>
<br>
Ha Quang Minh, Partha Niyogi and Yuan Yao.
<br>
In <i> Proc. of Computational Learning Theory (COLT),</i> 2006.<br>
[<a href="publications/MinNiyYao06.pdf">pdf</a>]
<p>
<li>
<B>Online Learning Algorithms.</B>
<br>
<a href="http://www.math.berkeley.edu/~smale/">Steve Smale</a> and Yuan Yao.
<br>
<i> Foundations of Computational Mathematics.</i> 2006, 6 (2): 145-170.
<br>
[<a href="publications/onlineI.pdf">pdf</a>]
<p>
</font>
</UL>
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<hr>
<p><font face="Arial, Helvetica, sans-serif"><b><font color="#660099", size=3>
Papers in Computer Vision, Machine Learning and Pattern Recognition</font></b></font></font>
-->
<ul>
<font size=2>
<li>
<B>Combining Flat and Structured Representations for Fingerprint Classification with Recursive Neural Networks and Support Vector Machines.</B>
<br>
Yuan Yao, Gian Luca Marcialis, <a href="http://www.cs.ucl.ac.uk/staff/M.Pontil/">Massimiliano Pontil</a>,
Paolo Frasconi, and Fablio Roli.
<br> <a href="http://www.elsevier.com/wps/find/journaldescription.cws_home/328/description#description"><i>Pattern Recognition</i></a>, 36(2): 397-406, 2003.
<br>
[<a href="https://github.com/yao-lab/publication/blob/master/yuan_massi_pr.pdf"> pdf </a>] [<a href="https://www.sciencedirect.com/science/article/pii/S0031320302000390"> link </a> ]
<p>
<li>
<B>A New Machine Learning Approach to Fingerprint Classification. </B>
<br>
Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil, Paolo Frasconi, and Fablio Roli.
<br>
In: <i>AI*IA 2001: Advances in Artificial Intelligence</i>, LNCS, vol.2175: 57-63.
<br>
[<a href="http://www.math.pku.edu.cn/teachers/yaoy/publications/yao01new.pdf"> pdf </a>]
<p>
<li>
<B>Fingerprint Classification with Combinations of Support Vector Machines. </B>
<br>
Yuan Yao, Massimiliano Pontil and Fablio Roli.
<br>
In: <i>Proceedings of Audio- and Video-Based Biometric Person Authentication, Third International Conference, AVBPA 2001</i>: 253-258.
<br>
<!--[<a href="publications/yao01fingerprint.pdf"> pdf </a>]-->[<a href="https://pdfs.semanticscholar.org/774b/d92725f33e9e4fb09084f18693009d1a9170.pdf"> link </a>]
<p>
<li>
<B>Multiscale Morphology for Color Images Implemented by Fuzzy Cellular Neural Network.</B>
<br>
Yuan Yao, Xiaofeng Zhang, Tianwen Zhang and Guangxiong Wang.
<br>
In: <i>Proceedings of IEEE Hong Kong Symposium on Robotics and Control</i>, July 1999, Hong Kong, pp. 459-462.
<p>
<li>
<B>Morphological Reconstruction for Color Images Implemented by Fuzzy Cellular Neural Networks.</B>
<br>
Yuan Yao, Guangxiong Wang and Tianwen Zhang.
<br>
<a href="http://cjc.ict.ac.cn"><i>Chinese Journal of Computers</i></a> (in Chinese), 22(7): 727-732, 1999.
<p>
<li>
<B>Application of Fuzzy Cellular Neural Networks to Stone Inscription Reconstruction in Chinese Calligraphy.</B>
<br>
Yuan Yao, Guangxiong Wang and Tianwen Zhang.
<br>
<a href="http://crad.ict.ac.cn/"><i>Journal of Computer Research and Development</i></a> (in Chinese), 36(3): 282-286, 1999. <p>
</font>
</ul>
</p>
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<hr>
<p><font face="Arial, Helvetica, sans-serif"><b><font color="#660099", size=3>
Papers in System and Control</font></b></font></font>
-->
<ul>
<font size=2>
<li>
<B>Global Optimal Robust Controller Design.</B>
<br>
Lianfeng Li, Guangxiong Wang and Yuan Yao.
<br>
<a href="http://www.jcta.ac.cn"><i>Journal of Control Theory and Applications</i></a> (in Chinese), 18(2): 266-269, 2001.
<p>
<li>
<B>On the Application Problem of the Gap Metric for SISO Systems.</B>
<br>
Yuan Yao, Lianfeng Li and Gejun Bao.
<br>
<a href="http://journal.hit.edu.cn"><i>Journal of Harbin Institute of Technology</i></a> (in Chinese), 31(6): 19-21, 1999.
<p>
<li>
<B>Optimal Robust Performance in Constantly Scaled H_infinity control.</B>
<br>
Yuan Yao, Jingbo Wang, Lianfeng Li and Guangxiong Wang.
<br>
In: <I>Korea-China Process System Engineering Workshop</I>. August 1999, Korea.
<p>
<li>
<B>Robust Gain-scheduled H_infinity control with Constant Diagonal Scaling. </B>
<br>
Yuan Yao, Lianfeng Li, Guangxiong Wang and Jingbo Wang.
<br>
In: <i>Proceedings of IEEE Hong Kong Symposium on Robotics and Control</i>, July 1999, Hong Kong, pp. 628-632.
<p>
<li>
<B>Application of Quadratic Stabilization, Constantly Scaled H_infinity control and mu-Synthesis. </B>
<br>
Xiaofeng Wang, Yuan Yao, Guangxiong Wang and Jingbo Wang.
<br>
In: <i>Proceedings of IEEE Hong Kong Symposium on Robotics and Control</i>, July 1999, Hong Kong, pp. 633-637.
<p>
<li>
<B>Identifying Noise Model in Closed-Loop Using Subspace Method.</B>
<br>
Jingbo Wang, Jibril Jiya, Tianyou Chai, Yuan Yao, Guangxiong Wang and Shijie Xu.
<br>
In: <I>Proceedings of the IEEE International Vehicle Electronics Conference (IVEC '99),</I> September 6-9, 1999, Changchun, China, pp. 349-351.
<p>
<li>
<B>FEM-Based Modeling in Servo Design.
</B>
<br>
Yuan Yao and Jing Luo.
<br>
<a href="http://emc.hrbust.edu.cn"><i>Electric Machine and Control</i></a> (in Chinese), 2(2): 108-111, 1998.
<p>
</font>
</ul>
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<p><font face="Arial, Helvetica, sans-serif"><b><font color="#660099", size=3>
Conference Talks/Poster Presentations</font></b></font></font>
<ul>
<font size=2>
<li>Yao, Y., J. Sun, X. Huang, V. Pande, L. Guibas and G. Carlsson (2008). Topological Methods for Exploring Biomolecular Folding Pathways, <I>the 9th Biomedical Computation at Stanford (BCATS)</I>, spotlight poster presentation, October 26, 2008, Stanford, CA.
<p>
<li> Sun, J., X. Huang, Y. Yao, G. Carlsson, V. Pande and L. Guibas (2008). A Well-controlled Fast Clustering Method on Conformation Space of Biomolecules, <I>the 9th Biomedical Computation at Stanford (BCATS)</I>, poster presentation, October 26, 2008, Stanford, CA.
<p>
<li> Bowman, G.~R., X. Huang, Y. Yao, J. Sun and V. Pande (2008). Adaptive Seeding: A New Method for Simulating Biologically Relevant Timescales, <I>the 9th Biomedical Computation at Stanford (BCATS)</I>, poster presentation, Stanford, October 26, 2008.
<p>
<li> <B>Combinatorial Hodge Theory and A Geometric Approach to Ranking</B>, <I>SIAM Annual Meeting, minisymposium: Mathematical Methods in Data Mining</I>, San Diego, July 7-11, 2008.
<p>
<li><B>Topological Methods for Exploring Low-density States in Biomolecular Folding Pathways,</B> <I>Modern Massive Data Sets (MMDS)</I>, Stanford, June 25-39, 2008.
<p>
<li><B>Hodge Decomposition, Spectral Embedding, and the Netflix Dataset</B>, <I>Bay Area Scientific Computing Day: honoring Professors Kahan and Parlett, MSRI</I>, Berkeley, March 29-30, 2008.
<p>
<li> Scheler, G. and Y. Yao (2007). Equilibria in neuroadaptive pathways.