World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9423
World Ranking
7501
National Ranking
3264

Research.com Recognitions

  • 2018 - Fellow of Alfred P. Sloan Foundation

Overview

Yihong Wu is affiliated with Yale University in the United States and has contributed extensively to the fields of computer science and mathematics. Their research covers a broad range of topics, emphasizing artificial intelligence, statistics and probability, and computer vision and pattern recognition.

The subfields in which they have published include:

  • Artificial Intelligence
  • Statistics and Probability
  • Computer Vision and Pattern Recognition
  • Statistical and Nonlinear Physics
  • Signal Processing

Wu's work spans several main topics such as:

  • Bayesian Methods and Mixture Models
  • Statistical Methods and Inference
  • Markov Chains and Monte Carlo Methods
  • Statistical Methods and Bayesian Inference
  • Graph Theory and Algorithms
  • Random Matrices and Applications
  • Machine Learning and Algorithms

They have a significant presence in publication venues, predominantly in:

  • arXiv (Cornell University)
  • The Annals of Statistics
  • IEEE Transactions on Information Theory
  • Probability Theory and Related Fields
  • Mathematical Statistics and Learning

Among their recent papers are:

  • "Heteroskedastic PCA: Algorithm, optimality, and applications" (2022), published in The Annals of Statistics
  • "Efficient random graph matching via degree profiles" (2020), published in Probability Theory and Related Fields
  • "Optimal rates of entropy estimation over Lipschitz balls" (2020), published in The Annals of Statistics
  • "Settling the Sharp Reconstruction Thresholds of Random Graph Matching" (2022), published in IEEE Transactions on Information Theory
  • "Optimal estimation of Gaussian mixtures via denoised method of moments" (2020), published in The Annals of Statistics

Frequent collaborators in their research include:

  • Jiaming Xu
  • Yury Polyanskiy
  • Sophie H. Yu
  • Cheng Mao
  • Pengkun Yang

Wu has also authored a book titled Information Theory, published by Cambridge University Press in 2024.

In recognition of their contributions, Wu was awarded the title of Fellow of the Alfred P. Sloan Foundation in 2018.

Best Publications

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

    Xiaomei Zhao;Yihong Wu;Guidong Song;Zhenye Li

  • Sparse PCA: Optimal rates and adaptive estimation

    T. Tony Cai;Zongming Ma;Yihong Wu

  • Estimation in Gaussian Noise: Properties of the Minimum Mean-Square Error

    Dongning Guo;Yihong Wu;Shlomo Shamai;Sergio Verdú

  • Achieving Exact Cluster Recovery Threshold via Semidefinite Programming

    Bruce Hajek;Yihong Wu;Jiaming Xu

  • Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation

    Yihong Wu;Pengkun Yang

  • Rényi Information Dimension: Fundamental Limits of Almost Lossless Analog Compression

    Yihong Wu;Sergio Verdú

  • Functional Properties of Minimum Mean-Square Error and Mutual Information

    Yihong Wu;S. Verdu

  • PnP Problem Revisited

    Yihong Wu;Zhanyi Hu

  • Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices.

    T. Tony Cai;Zongming Ma;Yihong Wu

  • Optimal Phase Transitions in Compressed Sensing

    Yihong Wu;S. Verdu

  • Computational barriers in minimax submatrix detection

    Zongming Ma;Yihong Wu

  • Optimal prediction of the number of unseen species

    Alon Orlitsky;Ananda Theertha Suresh;Yihong Wu

  • Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions

    Bruce Hajek;Yihong Wu;Jiaming Xu

  • Strong data-processing inequalities for channels and Bayesian networks

    Yury Polyanskiy;Yihong Wu

  • Image-based camera localization: an overview

    Yihong Wu;Fulin Tang;Heping Li

  • Camera Calibration from the Quasi-affine Invariance of Two Parallel Circles

    Yihong Wu;Haijiang Zhu;Zhanyi Hu;Fuchao Wu

  • Wasserstein Continuity of Entropy and Outer Bounds for Interference Channels

    Yury Polyanskiy;Yihong Wu

  • Chebyshev polynomials, moment matching, and optimal estimation of the unseen

    Yihong Wu;Pengkun Yang

  • MMSE Dimension

    Yihong Wu;S. Verdu

  • Dissipation of Information in Channels With Input Constraints

    Yury Polyanskiy;Yihong Wu

  • Computational lower bounds for community detection on random graphs

    Bruce Hajek;Yihong Wu;Jiaming Xu

Frequent Co-Authors

Bruce Hajek
Bruce Hajek University of Illinois at Urbana-Champaign
Sergio Verdu
Sergio Verdu Princeton University
Alon Orlitsky
Alon Orlitsky University of California, San Diego
Dongning Guo
Dongning Guo Northwestern University
Tsachy Weissman
Tsachy Weissman Stanford University
Jianwei Huang
Jianwei Huang Chinese University of Hong Kong, Shenzhen
Shlomo Shamai
Shlomo Shamai Technion – Israel Institute of Technology
Yoram Bresler
Yoram Bresler University of Illinois at Urbana-Champaign
David Tse
David Tse Stanford University

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