World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
43
Citations
10210
World Ranking
1670
National Ranking
91

Engineering and Technology

D-Index
43
Citations
10210
World Ranking
6035
National Ranking
1159

Overview

Yu-Hong Dai is affiliated with the Chinese Academy of Sciences in China and specializes in research primarily within the fields of Computer Science and Engineering. Their work focuses on areas such as Computer Networks and Communications, Numerical Analysis, Computational Mechanics, Computational Theory and Mathematics, and Electrical and Electronic Engineering.

The scientist's research topics include Sparse and Compressive Sensing Techniques, Advanced Optimization Algorithms Research, Optimization and Variational Analysis, Stochastic Gradient Optimization Techniques, Software-Defined Networks and 5G, Matrix Theory and Algorithms, and Vehicle Routing Optimization Methods.

Frequent collaborators in their research include Wei-Kun Chen, Xinwei Liu, Ya-Feng Liu, Yakui Huang, and Zhi-Quan Luo.

Yu-Hong Dai has contributed to a number of publications in reputable venues. The most frequent publication outlets are:

  • arXiv (Cornell University)
  • Journal of Global Optimization
  • SIAM Journal on Optimization
  • Optimization methods & software
  • Computational Optimization and Applications

Significant recent papers authored or co-authored by Yu-Hong Dai include:

  • "Psychological impact of the coronavirus disease 2019 (COVID-19) outbreak on healthcare workers in China," 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • "Optimal Network Slicing for Service-Oriented Networks With Flexible Routing and Guaranteed E2E Latency," 2021, IEEE Transactions on Network and Service Management
  • "Equipping the Barzilai--Borwein Method with the Two Dimensional Quadratic Termination Property," 2021, SIAM Journal on Optimization
  • "FGFR2 upregulates PAI-1 via JAK2/STAT3 signaling to induce M2 polarization of macrophages in colorectal cancer," 2023, Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
  • "Proximal-Like Incremental Aggregated Gradient Method with Linear Convergence Under Bregman Distance Growth Conditions," 2020, Mathematics of Operations Research

The scope of Yu-Hong Dai's work reflects integration of computational theory with real-world applications in network management, optimization algorithms, and biomedical-related studies. Through numerous contributions to specialized journals and preprint repositories, they engage in advancing methodologies in optimization and algorithms, alongside addressing complex challenges in computer networks and applied mathematics.

Best Publications

  • A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property

    Y. H. Dai;Y. Yuan

  • New Conjugacy Conditions and Related Nonlinear Conjugate Gradient Methods

    Y. H. Dai;Lizhi Liao

  • Projected Barzilai-Borwein methods for large-scale box-constrained quadratic programming

    Yu-Hong Dai;Roger Fletcher

  • Convergence Properties of the BFGS Algoritm

    Yu-Hong Dai

  • An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimization

    Y. H. Dai;Ya-Xiang Yuan

  • R-linear convergence of the Barzilai and Borwein gradient method

    Yu Hong Dai;Lizhi Liao

  • Nonlinear Conjugate Gradient Methods

    Yu‐Hong Dai

  • A Nonlinear Conjugate Gradient Algorithm with an Optimal Property and an Improved Wolfe Line Search

    Yu-Hong Dai;Cai-Xia Kou

  • Convergence Properties of Nonlinear Conjugate Gradient Methods

    Yuhong Dai;Jiye Han;Guanghui Liu;Defeng Sun

  • Coordinated Beamforming for MISO Interference Channel: Complexity Analysis and Efficient Algorithms

    Ya-Feng Liu;Yu-Hong Dai;Zhi-Quan Luo

  • On the nonmonotone line search

    Y. H. Dai

  • Gradient Methods with Adaptive Step-Sizes

    Bin Zhou;Li Gao;Yu-Hong Dai

  • Convergence properties of the Fletcher-Reeves method

    Y. H. Dai;Y. Yuan

  • The cyclic Barzilai-–Borwein method for unconstrained optimization

    Yu-Hong Dai;William W. Hager;Klaus Schittkowski;Hongchao Zhang

  • New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds

    Yu-Hong Dai;Roger Fletcher

  • Max-Min Fairness Linear Transceiver Design for a Multi-User MIMO Interference Channel

    Ya-Feng Liu;Yu-Hong Dai;Zhi-Quan Luo

  • All Real Eigenvalues of Symmetric Tensors

    Chun-Feng Cui;Yu-Hong Dai;Jiawang Nie

  • Joint Power and Admission Control via Linear Programming Deflation

    Ya-Feng Liu;Yu-Hong Dai;Zhi-Quan Luo

  • Barzilai-Borwein step size for stochastic gradient descent

    Conghui Tan;Shiqian Ma;Yu-Hong Dai;Yuqiu Qian

  • On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA Systems

    Ya-Feng Liu;Yu-Hong Dai

  • On restart procedures for the conjugate gradient method

    Yu Hong Dai;Lizhi Liao;Duan Li

Frequent Co-Authors

Ya-xiang Yuan
Ya-xiang Yuan Chinese Academy of Sciences
Zhi-Quan Luo
Zhi-Quan Luo Chinese University of Hong Kong, Shenzhen
Shiqian Ma
Shiqian Ma Rice University
Roger Fletcher
Roger Fletcher University of Dundee
Jiawang Nie
Jiawang Nie University of California, San Diego
Duan Li
Duan Li City University of Hong Kong
Shuzhong Zhang
Shuzhong Zhang University of Minnesota
Wenbin Liu
Wenbin Liu University of Kent
Xiaoqi Yang
Xiaoqi Yang Hong Kong Polytechnic University
Sven Nordholm
Sven Nordholm Curtin University

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