Xuan Wu
Institute for Interdisciplinary Information Sciences

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Education Background 

2008-2011 First High school in Fuzhou.

2011-2015 Special Pilot CS Class (Yao Class), Tsinghua University.

2015-2018 IIIS, Tsinghua University, Master.

2018-2022, Johns Hopkins University, Ph.D. 

 
About Me

I have broad interests in various areas from the TCS community including Computational Learning Theory, Approximation Algorithms, Property Testing, Coresets, and Sketches.

Awards

2010 Asia-Pacific Informatics Olympiad (APIO 2010) Gold Prize, Ranking 6 of all players.

2010 National Olympics of Informatics (NOI 2010) Silver Prize, Ranking 26 of all players,

2011 Chinese Mathematics Olympics (CMO 2011) Gold Prize, Ranking 11 of all players.

2011 Second Class, Tsinghua New Student Awards.

2017 National Scholarship, Master.

2021 MINDS Fellowship, Johns Hopkins University


Publications

(Authors are ordered alphabetically otherwise marked by (C) )

The Power of Uniform Sampling for Coresets. Vladimir Braverman, Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Robert Krauthgamer, Chris Schwiegelshohn, Mads Bech Toftrup, Xuan Wu. (FOCS 2022, to appear)

New Coresets for Projective Clustering and Applications. (C) Murad Tukan*, Xuan Wu*, Samson Zhou, Vladimir Braverman, Dan Feldman. (AISTATS 2022)

Coresets for Clustering with Missing Values. Vladimir Braverman, Shaofeng H.-C. Jiang, Robert Krauthgameer, Xuan Wu. (NeurIPS 2021 Spotlight )

Coresets for Clustering in Excluded-minor Graphs and Beyond.  Vladimir Braverman, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu. (SODA 2021)

Coresets for Clustering in Graphs of Bounded Treewidth. Daniel Baker, Vladimir Braverman, Lingxiao Huang, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu. (ICML 2020)

Coresets for Ordered Weighted Clustering. Vladimir Braverman, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu. (ICML 2019)

eps-Coresets for Clustering (with Outliers) in Doubling Metrics. Lingxiao Huang, Shaofeng H.-C. Jiang, Jian Li, Xuan Wu. The 59th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2018) 

Improved Algorithms for Learning Mixtures of Gaussians. Xuan Wu, Changzhi Xie. (NCTCS 2018)


Manuscripts

Wasserstein Identity Testing. Shichuan Deng, Wenzheng Li, Xuan Wu. 

Sample Complexity of Stochastic $k$-median with Gaussian Noise.  Lingxiao Huang,  Xuan Wu. 

  

Talks and Slides
Coresets for Ordered Weighted Clustering. ICML 2019
Coresets for Clustering in Graphs of Bounded Treewidth. ICML 2020

Coresets for Clustering in Excluded-minor Graphs and Beyond. SODA 2021 

Coresets for Clustering with Missing Values.  NeurIPS 2021, Spotlight Presentation

 

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