Yudong Chen -- Publications by type

Preprint | Journal | Conference


Preprints


Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
Dong Yin, Yudong Chen, Kannan Ramchandran, and Peter Bartlett.
Preprint, 2018. [arxiv]

The Leave-one-out Approach for Matrix Completion: Primal and Dual Analysis
Lijun Ding and Yudong Chen.
Preprint, 2018. [arxiv]

Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm
Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, and Shuicheng Yan.
Preprint, 2018. [arxiv]

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

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



Journals


Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes
Dong Yin, Ramtin Pedarsani, Yudong Chen, and Kannan Ramchandran.
IEEE Transactions on Information Theory, to appear, 2018. [arxiv]

Exponential error rates of SDP for block models: Beyond Grothendieck's inequality
Yingjie Fei, and Yudong Chen.
IEEE Transactions on Information Theory, to appear, 2018. [arxiv]

Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation
Yudong Chen, and Yuejie Chi.
IEEE Signal Processing Magazine, vol. 35, no. 4, pp. 14-31, 2018. [arxiv] [ieee link]

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models
Yudong Chen, Xiaodong Li, and Jiaming Xu.
Annals of Statistics, vol. 46, no. 4, pp. 1573-1602, 2018. [arxiv] [web page and code]

Convex and Nonconvex Formulations for Mixed Regression with Two Components: Minimax Optimal Rates
Yudong Chen, Xinyang Yi, and Constantine Caramanis.
IEEE Transactions on Information Theory, vol. 64, no. 3, pp. 1738-1766, 2018. [ieee link]

Clustering from General Pairwise Observations with Applications to Time-varying Graphs
Shiau Hong Lim, Yudong Chen, and Huan Xu.
Journal of Machine Learning Research (JMLR), 18(49), 1-47, 2017. [pdf] [jmlr 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]

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]

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]

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.


Conference Proceedings


Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin, Yudong Chen, Kannan Ramchandran, and Peter Bartlett.
International Conference on Machine Learning (ICML), 2018. [arxiv]

Hidden Integrality of SDP Relaxation for Sub-Gaussian Mixture Models
Yingjie Fei and Yudong Chen.
Conference on Learning Theory (COLT), 2018. [arxiv]

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Yudong Chen, Lili Su, and Jiaming Xu.
ACM SIGMETRICS, 2018. [paper link] [arxiv]

Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes
Dong Yin, Ramtin Pedarsani, Yudong Chen, and Kannan Ramchandran.
The 55th Annual Allerton Conference on Communication, Control, and Computing, 2017.

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]

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]

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]

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.

Mining for Similarities in Urban Traffic Flow Using Wavelets
Yudong Chen, Yi Zhang, Jianming Hu, and Li Li.
IEEE International Conference on Intelligent Transportation System (ITSC‘07), 2007.

A Transportation Facilities Management Tree Model Based on IPv6
Zhiheng Li, Zuo Zhang, Qian Chen, and Yudong Chen.
IEEE International Conference on Intelligent Transportation System (ITSC’07), 2007.

Pattern Discovering of Regional Traffic Status with Self-Organizing Maps
Yudong Chen, Yi Zhang, and Jianming Hu.
IEEE International Conference on Intelligent Transportation System (ITSC’06), 2006.


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