Yihong Wu

Research interests

I am broadly interested in the theoretical and algorithmic aspects of high-dimensional statistics, information theory, and optimization.

Recent papers

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

• Cheng Mao, Yihong Wu, Jiaming Xu, and Sophie H. Yu, "Random graph matching at Otter's threshold via counting chandeliers", Sep 2022.

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

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

• Cheng Mao, Yihong Wu, Jiaming Xu, and Sophie H. Yu, "Testing network correlation efficiently via counting trees", Oct 2021.
  [George Nicholson Student Paper Competition finalist, INFORMS 2022. Congrats Sophie!]

• 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.

• Jian Ding, Yihong Wu, Jiaming Xu, and Dana Yang, "The planted matching problem: Sharp threshold and infinite-order phase transition", Mar 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.