Yudong Chen    

Photo

Assistant Professor
School of Operations Research and Information Engineering
Cornell University
223 Frank H.T. Rhodes Hall, Ithaca, NY 14853
Phone: (607) 255-0698   Fax: (607) 255-9129
yudong.chen at cornell dot edu

[Bio]  [Publications (chronological order) (by topic) (by type)]  [Teaching]

News

I co-organized the ICML workshop on Non-convex Analysis and Optimization held on June 23rd, 2016 in New York City.

Bio

I am an assistant professor in the School of Operations Research and Information Engineering (ORIE) at Cornell University (also a field member of Computer Science and Statistics). My research interests include machine learning, high-dimensional and robust statistics, and optimization. Some of the topics that I am interested in are: sparse recovery and compressed sensing, robust matrix completion and PCA, graph clustering and community detection in networks, mixture problems, large-scale learning and optimization, computational and statstistical tradeoffs, and non-convex statistical algorithms.

I obtained my Ph.D. in Electrical and Computer Engineering in 2013 from The University of Texas at Austin, advised by Constantine Caramanis. From 2013 to 2015 I was a postdoc in the EECS department at the University of California, Berkeley hosted by Martin J. Wainwright. In 2014 and 2015 I was a visiting scholar at the National University of Singapore. I received my B.S. and M.S. from Tsinghua University. I worked as an intern at Raytheon BBN, IBM and Siemens.

Publications (chronological order)

(See publications by type, publications by topic, and my Google Scholar page)

Clustering from General Pairwise Observations with Applications to Time-varying Graphs,
Shiau Hong Lim, Yudong Chen, and Huan Xu
Submitted to Journal of Machine Learning Research (JMLR), 2016.
Partial preliminary resutls appeared in ICML and NIPS.

Fast Algorithms for Robust PCA via Gradient Descent,
Xinyang Yi, Dohyung Park, Yudong Chen, and Constantine Caramanis
Neural Information Processing Systems Conference (NIPS), 2016. [arxiv] [code]

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models,
Yudong Chen, Xiaodong Li, and Jiaming Xu
Submitted to Annals of Statistics, 2015. [arxiv] [web page and code]

Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees,
Yudong Chen, Martin J. Wainwright.
Preprint, 2015. [arXiv]

Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization,
Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, and Shuicheng Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [pdf]

A Convex Optimization Framework for Bi-Clustering,
Shiau Hong Lim, Yudong Chen, and Huan Xu.
International Conference on Machine Learning (ICML), 2015. [pdf] [supplementary] [icml link]

Matrix Completion with Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs,
Yudong Chen, Huan Xu, Constantine Caramanis, and Sujay Sanghavi.
IEEE Transactions on Information Theory, vol. 62, no. 1, pp. 503-526, 2016. [arxiv] [ieee link]

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices,
Yudong Chen and Jiaming Xu.
Journal of Machine Learning Research (JMLR), vol. 17, no. 27, pp. 1-57, 2016. [pdf] [arXiv]

Completing Any Low-Rank Matrix, Provably,
Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, and Rachel Ward.
Journal of Machine Learnng Research (JMLR), vol. 16, pp. 2999-3034, 2015. [pdf] [jmlr link]

Incoherence-Optimal Matrix Completion,
Yudong Chen.
IEEE Transactions on Information Theory, vol. 61, no. 5, pp. 2909-2923, 2015. [ieee link] [arXiv]

Iterative and Active Graph Clustering Using Trace Norm Minimization Without Cluster Size Constraints,
Nir Ailon, Yudong Chen, and Huan Xu.
Journal of Machine Learning Research (JMLR), vol. 16, pp. 450-490, 2015. [pdf] [jmlr link] [arXiv]

Improved Graph Clustering,
Yudong Chen, Sujay Sanghavi and Huan Xu.
IEEE Transactions on Information Theory, vol. 60, no. 10, pp. 6440–6455, 2014. [ieee link] [arXiv]

Clustering Partially Observed Graphs via Convex Optimization,
Yudong Chen, Ali Jalali, Sujay Sanghavi, and Huan Xu.
Journal of Machine Learning Research (JMLR), vol. 15, pp. 2213-2238, 2014. [pdf] [arXiv]

Clustering from Labels and Time-Varying Graphs
Shiau Hong Lim, Yudong Chen, and Huan Xu.
Neural Information Processing Systems Conference (NIPS), 2014 (Spotlight). [pdf] [supplementary] [nips link]

Weighted Graph Clustering with Non-uniform Uncertainties,
Yudong Chen, Shiau Hong Lim, and Huan Xu.
International Conference on Machine Learning (ICML), 2014. [pdf] [supplementary] [icml link]

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting,
Yudong Chen and Jiaming Xu.
International Conference on Machine Learning (ICML), 2014.

Coherent Matrix Completion,
Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, and Rachel Ward.
International Conference on Machine Learning (ICML), 2014.

A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates,
Yudong Chen, Xinyang Yi, and Constantine Caramanis.
Conference on Learning Theory (COLT), 2014. [arxiv] [colt pdf]

Low-rank Matrix Recovery from Errors and Erasures,
Yudong Chen, Ali Jalali, Sujay Sanghavi, and Constantine Caramanis.
IEEE Transactions on Information Theory, vol. 59, no. 7, pp. 4324-4337, 2013. [ieee link] [arXiv]

Detecting Overlapping Temporal Community Structure in Time-Evolving Networks,
Yudong Chen, Vikas Kawadia, and Rahul Urgaonkar.
Technical Report, 2013. [arXiv]

User Association for Load Balancing in Heterogeneous Cellular Networks,  
Qiaoyang Ye, Beiyu Rong, Yudong Chen, Mazin Al-Shalash, Constantine Caramanis, and Jeffrey G. Andrews.
IEEE Transactions on Wireless Communications, vol. 12, no. 6, pp. 2706-2716, 2013. [ieee link] [arXiv]

Breaking the Small Cluster Barrier of Graph Clustering,
Nir Ailon, Yudong Chen, and Huan Xu.
International Conference on Machine Learning (ICML), 2013.

Robust Sparse Regression under Adversarial Corruption,
Yudong Chen, Constantine Caramanis, and Shie Mannor.
International Conference on Machine Learning (ICML), 2013. [pdf] [supplementary]

Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery,
Yudong Chen and Constantine Caramanis.
International Conference on Machine Learning (ICML), 2013. [pdf] [supplementary]

Clustering Sparse Graphs,
Yudong Chen, Sujay Sanghavi and Huan Xu.
In Advances in Neural Information Processing Systems 25 (NIPS), 2012. 

Towards an Optimal User Association in Heterogeneous Cellular Networks,
Qiaoyang Ye, Beiyu Rong, Yudong Chen, Mazin Al-Shalash, Constantine Caramanis, and Jeffrey G. Andrews.
IEEE Globecom, 2012.

Low-rank Matrix Recovery from Errors and Erasures,
Yudong Chen, Ali Jalali, Sujay Sanghavi, and Constantine Caramanis.
International Symposium on Information Theory (ISIT), 2011.

Clustering Partially Observed Graphs via Convex Optimization,
Ali Jalali, Yudong Chen, Sujay Sanghavi, and Huan Xu.
International Conference on Machine Learning (ICML), 2011.

Robust Matrix Completion with Corrupted Columns,
Yudong, Chen, Huan Xu, Constantine Caramanis, and Sujay Sanghavi.
International Conference on Machine Learning (ICML), 2011.

Quantization Errors of Uniformly Quantized fGn and fBm Signals,
Zhiheng Li, Yudong Chen, Li Li, and Yi Zhang.
IEEE Signal Processing Letters, vol. 16, no. 12, 1059-1062, 2009. [arXiv]

PCA Based Hurst Exponent Estimator for fBm Signals under Disturbances,
Li Li, Jianming Hu, Yudong Chen, and Yi Zhang.
IEEE Transactions on Signal Processing, vol. 57, no. 7, 2840-2846, 2009.

Teaching

ORIE 6700 Statistical Principles (Fall 2016 syllabus; Fall 2015)

ORIE 4740 Statistical Data Mining I (Spring 2016 syllabus)