Qingjie Hu

According to our database1, Qingjie Hu authored at least 15 papers between 2005 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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Bibliography

2025
A modified Polak-Ribière-Polyak type conjugate gradient method for vector optimization.
Optim. Methods Softw., July, 2025

A vector restricted variant MVHS+ CG method based algorithm for unconstrained vector optimization problems.
J. Comput. Appl. Math., 2025

Generalizing Key Recovery Attacks Against NTRU with Multiple Keys and Its Application in NTRUReEncrypt.
Proceedings of the Cryptology and Network Security - 24th International Conference, 2025

2024
On the Extension of Dai-Liao Conjugate Gradient Method for Vector Optimization.
J. Optim. Theory Appl., October, 2024

Alternative extension of the Hager-Zhang conjugate gradient method for vector optimization.
Comput. Optim. Appl., May, 2024

2023
A class of improved conjugate gradient methods for nonconvex unconstrained optimization.
Numer. Linear Algebra Appl., August, 2023

2020
An active set Barzilar-Borwein algorithm for l<sub>0</sub> regularized optimization.
J. Glob. Optim., 2020

New dualities for mathematical programs with vanishing constraints.
Ann. Oper. Res., 2020

2019
A fast conjugate gradient algorithm with active set prediction for ℓ1 optimization.
Optim. Methods Softw., 2019

2017
On an l<sub>1</sub> exact penalty result for mathematical programs with vanishing constraints.
Optim. Lett., 2017

2013
Generalization of an existence theorem for complementarity problems.
J. Comput. Appl. Math., 2013

2012
Second-order duality for non-differentiable minimax fractional programming.
Int. J. Comput. Math., 2012

2008
Quadratically constraint quadratical algorithm model for nonlinear minimax problems.
Appl. Math. Comput., 2008

2006
A new superlinearly convergent norm-relaxed method of strongly sub-feasible direction for inequality constrained optimization.
Appl. Math. Comput., 2006

2005
A new norm-relaxed method of strongly sub-feasible direction for inequality constrained optimization.
Appl. Math. Comput., 2005


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