Preprints

• Andre Wibisono, Yihong Wu, Kaylee Yingxi Yang, "Optimal score estimation via empirical Bayes smoothing", Feb 2024.

• Leon Lufkin, Yihong Wu, Jiaming Xu, "Sharp Information-Theoretic Thresholds for Shuffled Linear Regression", Feb 2024.

• Zhou Fan, Leying Guan, Yandi Shen, Yihong Wu, "Gradient flows for empirical Bayes in high-dimensional linear models", Dec 2023.

• Yutong Nie and Yihong Wu, "Large-scale multiple testing: Fundamental limits of false discovery rate control and compound oracle?", Feb 2023.

• Yandi Shen and Yihong Wu, "Empirical Bayes estimation: When does -modeling beat -modeling in theory (and in practice)?", Nov 2022.

• Soham Jana, Yury Polyanskiy, and Yihong Wu, "Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods", Oct 2022.

• Yury Polyanskiy and Yihong Wu, "Sharp regret bounds for empirical Bayes and compound decision problems", Sep 2021.

• Zhou Fan and Yihong Wu, "The replica-symmetric free energy for Ising spin glasses with orthogonally invariant couplings", May 2021.

• Yury Polyanskiy and Yihong Wu, "Note on approximating the Laplace transform of a Gaussian on a complex disk", Aug 2020.

• Yury Polyanskiy and Yihong Wu, "Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models", Aug 2020.

• Yury Polyanskiy and Yihong Wu, "Dualizing Le Cam's method, with applications to estimating the unseens", Feb 2019.

Monographs and book chapters

• Yihong Wu and Pengkun Yang, "Polynomial methods in statistical inference: theory and practice", Foundations and Trends® in Communications and Information Theory, Vol. 17, No. 4, pp 402-586, 2020. [arxiv]

• Yihong Wu and Jiaming Xu, "Statistical Problems with Planted Structures: Information-Theoretical and Computational Limits", to appear in Information-Theoretic Methods in Data Science, edited by Yonina Eldar and Miguel Rodrigues, Cambridge University Press, 2018.

• Yury Polyanskiy and Yihong Wu, "Strong data-processing inequalities for channels and Bayesian networks", in Convexity, Concentration and Discrete Structures, IMA Volumes in Mathematics and its Applications, vol. 161, Springer, 2017.

Publications

• Cheng Mao, Yihong Wu, Jiaming Xu, and Sophie H. Yu, "Random graph matching at Otter's threshold via counting chandeliers", Proceedings of the 55th Annual ACM Symposium on Theory of Computing (STOC), 2023.

• Jian Ding, Yihong Wu, Jiaming Xu, and Dana Yang, "The planted matching problem: Sharp threshold and infinite-order phase transition", Probability Theory and Related Fields Article, 2023.

• Cheng Mao, Yihong Wu, Jiaming Xu, and Sophie H. Yu, "Testing network correlation efficiently via counting trees", The Annals of Statistics, 2024.
  [George Nicholson Student Paper Competition finalist, INFORMS 2022.]

• Soham Jana, Yury Polyanskiy, Anzo Teh, and Yihong Wu, "Empirical Bayes via ERM and Rademacher complexities: the Poisson model", Conference on Learning Theory (COLT), 2023.

• Zeyu Jia, Yury Polyanskiy, and Yihong Wu, "Entropic characterization of optimal rates for learning Gaussian mixtures", Conference on Learning Theory (COLT), 2023.

• Yun Ma, Yihong Wu, and Pengkun Yang, "On the best approximation by finite Gaussian mixtures", 2023 IEEE International Symposium on Information Theory (ISIT), 2023, pp. 2619–2624.

• Haoyu Wang, Yihong Wu, Jiaming Xu, and Israel Yolou, "Random Graph Matching in Geometric Models: the Case of Complete Graphs", Conference on Learning Theory (COLT), 2022.

• Natalie Doss, Yihong Wu, Pengkun Yang, and Harrison H. Zhou, "Optimal estimation of high-dimensional Gaussian mixtures", The Annals of Statistics, 2023.

• Yihong Wu, Jiaming Xu and Sophie H. Yu, "Testing correlation of unlabeled random graphs", The Annals of Applied Probability, 2023.

• Yihong Wu, Jiaming Xu, and Sophie H. Yu, "Settling the Sharp Reconstruction Thresholds of Random Graph Matching", IEEE Transactions on Information Theory, 2022. [ISIT]

• Cheng Mao and Yihong Wu, "Learning Mixtures of Permutations: Groups of Pairwise Comparisons and Combinatorial Method of Moments", The Annals of Statistics, 2022.

• Yihong Wu and Harrison H. Zhou, "Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in iterations", Mathematical Statistics and Learning, 4 (2021), 143–220.

• Zhou Fan, Cheng Mao, Yihong Wu, and Jiaming Xu, "Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model", Foundations of Computational Mathematics, Jun 2022. [code] [ICML]

• Zhou Fan, Cheng Mao, Yihong Wu, and Jiaming Xu, "Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality", Foundations of Computational Mathematics, Jun 2022.

• Yanjun Han, Soham Jana, and Yihong Wu, "Optimal prediction of Markov chains with and without spectral gap", Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021.

• Zhou Fan, Yi Sun, Tianhao Wang, Yihong Wu. "Likelihood landscape and maximum likelihood estimation for the discrete orbit recovery model", Communications on Pure and Applied Mathematics, Jul 2023.

• Jian Ding, Zongming Ma, Yihong Wu, and Jiaming Xu, "Efficient random graph matching via degree profiles", Probability Theory and Related Fields, 2020.

• Anru Zhang, T. Tony Cai, Yihong Wu, "Heteroskedastic PCA: Algorithm, Optimality, and Applications", The Annals of Statistics, Vol. 50, No. 1, 53–80, 2022.

• Jian Ding, Yihong Wu, Jiaming Xu, and Dana Yang "Consistent recovery threshold of hidden nearest neighbor graphs", Conf. on Learning Theory (COLT), 2020.

• Soham Jana, Yury Polyanskiy and Yihong Wu, "Extrapolating the profile of a finite population", Conf. on Learning Theory (COLT), May 2020.

• Yury Polyanskiy and Yihong Wu, "Application of information-percolation method to reconstruction problems on graphs", to appear in Mathematical Statistics and Learning], Jun 2018.

• Yihong Wu and Pengkun Yang, "Optimal estimation of Gaussian mixtures via denoised method of moments", The Annals of Statistics, vol. 48, no. 4, pp. 1981-2007, 2020. [code]

• Jason M. Klusowski and Yihong Wu, "Estimating the Number of Connected Components in a Graph via Subgraph Sampling", Beroulli, vol. 26, no. 3, pp. 1635–1664, Feb 2020.

• T. Tony Cai and Yihong Wu, "Statistical and Computational Limits for Sparse Matrix Detection", The Annals of Statistics, vol. 48, no. 3, pp. 1593-1614, 2020.

• Yanjun Han, Jiantao Jiao, Tsachy Weissman, and Yihong Wu, "Optimal Rates of Entropy Estimation over Lipschitz Balls", The Annals of Statistics, Nov 2020.

• Vivek Bagaria, Jian Ding, David Tse, Yihong Wu, and Jiaming Xu, "Hidden Hamiltonian Cycle Recovery via Linear Programming", Operations Research, volume 68, number 1, Jan 2020.

• Yihong Wu and Pengkun Yang, "Chebyshev polynomials, moment matching, and optimal estimation of the unseen", The Annals of Statistics, Volume 47, Number 2, pp. 857-883, 2019. [code]

• Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, and Yihong Wu, "Data Amplification: A Unified and Competitive Approach to Property Estimation", NIPS, 2018.

• Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, and Tiancheng Yu, "Entropy Rate Estimation for Markov Chains with Large State Space", NIPS, 2018.

• Jason M. Klusowski and Yihong Wu, "Counting Motifs with Graph Sampling", Conf. on Learning Theory (COLT), Jul 2018.

• Yihong Wu and Pengkun Yang, "Sample complexity of the distinct elements problem", Mathematical Statistics and Learning, Volume 1, Issue 1, pp. 37-72, 2018.

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Submatrix localization via message passing", Journal of Machine Learning Research, 18(186):1−52, Oct 2018.

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Recovering a Hidden Community Beyond the Kesten–Stigum threshold in Time", Journal of Applied Probability, Volume 55, Issue 2, pp. 325-352, Jun 2018.

• Ashok Vardhan Makkuva and Yihong Wu, "Equivalence of additive-combinatorial linear inequalities for Shannon entropy and differential entropy", IEEE Transactions on Information Theory, vol. 64, no. 5, pp. 3579 - 3589, May 2018.

• Flavio P. Calmon, Yury Polyanskiy, and Yihong Wu, "Strong data processing inequalities for input constrained additive noise channels", IEEE Transactions on Information Theory, vol. 64, no. 3, pp. 1879-1892, Mar 2018.

• Kiryung Lee, Yihong Wu, and Yoram Bresler, "Near optimal compressed sensing of sparse rank-one matrices via sparse power factorization", IEEE Transactions on Information Theory, vol. 64, no. 3, pp. 1666-1698, Mar 2018.

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Information Limits for Recovering a Hidden Community", IEEE Transactions on Information Theory, vol. 63, no. 8, pp. 4729-4745, Aug 2017.

• Yury Polyanskiy, Ananda Theertha Suresh and Yihong Wu, "Sample complexity of population recovery", Conf. on Learning Theory (COLT), Jul 2017.

• Alon Orlitsky, Ananda Theertha Suresh, and Yihong Wu, "Optimal prediction of the number of unseen species", Proceedings of the National Academy of Sciences, vol. 113, no. 47, pp. 13283–13288, Nov 2016. [paper] [supplement]
  (For a full account and a better title, see "Estimating the number of unseen species: A bird in the hand is worth in the bush", draft, Nov 2015.)

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions", IEEE Transactions on Information Theory, vol. 62, no. 10, pp.5918-5937, Oct 2016.

• Yury Polyanskiy and Yihong Wu, "Wasserstein continuity of entropy and outer bounds for interference channels", IEEE Trans. Inf. Theory, vol. 62, no. 7, pp. 3992–4002, Jul. 2016. [isit] [Simons Institute research vignette]

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Semidefinite Programs for Exact Recovery of a Hidden Community", Conf. on Learning Theory (COLT), Jun 2016. [arxiv]

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Achieving Exact Cluster Recovery Threshold via Semidefinite Programming", IEEE Transactions on Information Theory, vol. 62, no. 5, pp. 2788–2797, May 2016. [isit]

• Yihong Wu and Pengkun Yang, "Minimax rates of entropy estimation on large alphabets via best polynomial approximation", IEEE Transactions on Information Theory, vol. 62, no. 7, June 2016. [entropy estimator code] [isit]

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Exact recovery threshold in the binary censored block model", Information Theory Workshop (ITW) 2015, Jeju Island, Korea, Jun 2015 (invited).

• Bruce Hajek, Yihong Wu, and Jiaming Xu, "Computational Lower Bounds for Community Detection on Random Graphs", Conf. on Learning Theory (COLT), Jun 2015. [arxiv]

• Yury Polyanskiy and Yihong Wu, "Dissipation of information in channels with input constraints", IEEE Transactions on Information Theory, vol. 62, no. 1, pp. 35–55, Jan 2016.

• Zongming Ma and Yihong Wu, "Volume ratio, sparsity, and minimaxity under unitarily invariant norms", IEEE Transactions on Information Theory, vol. 61, no. 12, pp. 6939 - 6956, Dec 2015. [isit]

• Zongming Ma and Yihong Wu, "Computational barriers in minimax submatrix detection", The Annals of Statistics, vol. 43, No. 3, pp. 1089 - 1116 2015.

• Yihong Wu, Shlomo Shamai (Shitz), and Sergio Verdú, "Information Dimension and the Degrees of Freedom of the Interference Channel", IEEE Transactions on Information Theory, vol. 61, no. 1, pp. 256 - 279, Jan 2015. [isit]

• T. Tony Cai, Zongming Ma and Yihong Wu, "Optimal estimation and rank detection for sparse spiked covariance matrices", Probability Theory and Related Fields, vol. 161, no. 3-4, pp 781-815, Apr 2015.

• Yury Polyanskiy and Yihong Wu, "Peak-to-average power ratio of good codes for Gaussian channel", IEEE Transactions on Information Theory, vol. 60, no. 12, pp. 7655 - 7660, Nov 2014.

• T. Tony Cai and Yihong Wu, "Optimal Detection of Sparse Mixtures Against a Given Null Distribution", IEEE Transactions on Information Theory, vol. 60, no. 4, pp. 2217 - 2232, Apr 2014. [arxiv]

• T. Tony Cai, Zongming Ma and Yihong Wu, "Sparse PCA: Optimal rates and adaptive estimation", The Annals of Statistics, vol. 41, no. 6, pp. 3074 - 3110, 2013.

• Alexandr Andoni, Huy L. Nguyen, Yury Polyanskiy and Yihong Wu, "Tight lower bound for linear sketches of moments", 40th Internat. Coll. Automata, Languages, and Programming (ICALP-2013), Riga, Latvia, Jul 2013.

• Yihong Wu and Sergio Verdú, "Optimal Phase Transitions in Compressed Sensing", IEEE Transactions on Information Theory, vol. 58, no. 10, pp. 6241 – 6263, Jul 2012. [arxiv] [isit]

• Yihong Wu and Sergio Verdú, "Functional Functional Properties of MMSE and Mutual Information", IEEE Transactions on Information Theory, vol. 58, no. 3, pp. 1289 – 1301, Mar 2012. [isit]

• Erik Ordentlich, Marelo Weinberger, and Yihong Wu, "Piecewise constant prediction", in Proceedings of 2012 IEEE International Symposium on Information Theory, Boston, MA, USA, Jul 2012.

• Yihong Wu and Sergio Verdú, "MMSE Dimension", IEEE Transactions on Information Theory, vol. 57, no. 8, pp. 4857 – 4879, Aug 2011. [isit]

• Yihong Wu, Dongning Guo, and Sergio Verdú, "Derivative of Mutual Information at Zero SNR: the Gaussian Noise Case", IEEE Transactions on Information Theory, pp. 1 – 6, Jul 2011.

• Yihong Wu and Sergio Verdú, "Witsenhausen's Counterexample: a View from Optimal Transport Theory", 50th IEEE Conference on Decision and Control, Orlando, FL, Dec 2011.

• Yihong Wu, Erik Ordentlich, and Marelo Weinberger, "Energy-driven Lossless Data Compression: Rate-variability Tradeoff", 2011 IEEE International Symposium on Information Theory, Saint Petersburg, Russia, Aug 2011.

• Yihong Wu and Sergio Verdú, "The impact of constellation cardinality on Gaussian channel capacity", Forty-Eighth Annual Allerton Conference on Communication, Control, and Computing, September 29 – October 1, 2010, Monticello, IL (invited).

• Dongning Guo, Yihong Wu, Shlomo Shamai (Shitz) and Sergio Verdú, "Estimation in Gaussian Noise: Properties of the Minimum Mean-Square Error", IEEE Transactions on Information Theory, vol. 57, no. 4, pp. 1 – 15, May 2011.

• Yihong Wu and Sergio Verdú, "Rényi Information Dimension: Fundamental Limits of Almost Lossless Analog Compression", IEEE Transactions on Information Theory, Vol. 56, No. 8, pp. 3721 – 3748, Aug 2010. [isit]

• Kai Yang, Yihong Wu, Jianwei Huang, Xiaodong Wang and Sergio Verdú, "Distributed Robust Optimization for Communication Networks", Proc. IEEE Conference on Computer Communications (INFOCOM), Phoenix, AZ, Apr 2008.

• Yihong Wu, Xiaobo Chen, Lin Zhang, Zhisheng Niu, "Interest Dissemination with Directional Antenna for Wireless Sensor Networks with Mobile Sinks", Proc. ACM Conference on Embedded Networked Sensor Systems (SenSys), Boulder, CO, October, 2006.

Thesis

• Yihong Wu, "Shannon Theory for Compressed Sensing ", Ph.D. dissertation, Dept. Electrical Engineering, Princeton University, Sep 2011