Yudong Chen -- Publications by type
Preprint | Journal
| ConferenceLikelihood Landscape and Local Minima Structures of Gaussian Mixture Models
Yudong Chen and Xumei Xi
Preprint, 2020. [arxiv]
Structures of Spurious Local Minima in k-means
Wei Qian, Yuqian Zhang, and Yudong Chen
Preprint, 2020. [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]
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond
Fanghui Liu, Xiaolin Huang, Yudong Chen, and Johan A.K. Suykens
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), to appear, 2021 [arxiv]
Low-rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence
Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Diaz, Lijun Ding, and Dmitriy Drusvyatskiy.
Foundations of Computational Mathematics, to appear, 2019. [arxiv]
The Leave-one-out Approach for
Matrix Completion: Primal and Dual Analysis
Lijun
Ding and Yudong Chen.
IEEE Transactions on Information Theory, 2019. [arxiv] [ieee link]
Achieving the Bayes Error Rate in Synchronization and Block Models by SDP, Robustly
Yingjie Fei and Yudong Chen.
IEEE Transactions on Information Theory, vol. 66, no. 6, pp. 3929-3953, 2020. [arxiv] [ieee link]
Convex Relaxation Methods for Community Detection
Xiaodong Li, Yudong Chen, and Jiaming Xu.
Statistical Science, vol. 36, no. 1, pp. 2-15, 2021. [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.
IEEE Transactions on Pattern Analysis and Machine Intelligence
(T-PAMI), vol. 42, no. 4, pp. 925-938, 2020. [arxiv]
[ieee
link]
Learning Mixtures of Sparse Linear
Regressions Using Sparse Graph Codes
Dong Yin, Ramtin Pedarsani, Yudong Chen, and Kannan Ramchandran.
IEEE Transactions on Information Theory, vol. 65, no. 3, pp. 1430-1451,
2019. [arxiv] [ieee link]
Exponential error rates of SDP for
block models: Beyond Grothendieck's inequality
Yingjie Fei, and Yudong Chen.
IEEE Transactions on Information Theory, vol. 65, no. 1, pp. 551-571,
2019. [arxiv] [ieee link]
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.
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, and Qiaomin Xie
Neural Information Processing Systems Conference (NeurIPS), 2020. (Spotlight) [arxiv]
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium
Qiaomin Xie, Yudong Chen, Zhaoran Wang, and Zhuoran Yang
Conference on Learning Theory (COLT), 2020. [arxiv]
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, and Johan Suykens
Association for the Advancement of Artificial Intelligence Conference (AAAI), 2020. [arxiv]
Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
Wei Qian, Yuqian Zhang, and Yudong Chen.
Neural Information Processing Systems Conference (NeurIPS), 2019. [arxiv]
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery
Jicong Fan, Lijun Ding, Yudong Chen, and Madeleine Udell
Neural Information Processing Systems Conference (NeurIPS), 2019. [arxiv]
Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly
Yingjie Fei and Yudong Chen.
Conference on Learning Theory (COLT), 2019. [colt pdf]
Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression
Jeongyeol Kwon, Wei Qian, Constantine Caramanis, Yudong Chen, and Damek Davis.
Conference on Learning Theory (COLT), 2019. [arxiv]
Defending Against Saddle Point
Attack in Byzantine-Robust Distributed Learning
Dong Yin, Yudong Chen, Kannan Ramchandran, and Peter Bartlett.
International Conference on Machine Learning (ICML), 2019 (long talk). [arxiv]
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]
2nd Place, 2018 INFORMS George Nicholson Student Paper Competition.
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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