Zobrazeno 1 - 10
of 481
pro vyhledávání: '"Qin, Xiaolong"'
Establishing explicit formulas of coderivatives with respect to a set of the normal cone mapping to a polyhedron, the solution set of a variational inequalities system, is one of the main goals of this paper. By using our coderivative formulas, we pr
Externí odkaz:
http://arxiv.org/abs/2312.15834
This paper provides formulas for calculating of Fr\'{e}chet and limiting normal cones with respect to a set of sets and the limiting coderivative with respect to a set of set-valued mappings. These calculations are obtained under some qualification c
Externí odkaz:
http://arxiv.org/abs/2311.08741
The notions and certain fundamental characteristics of the proximal and limiting normal cones with respect to a set are first presented in this paper. We present the ideas of the limiting coderivative and subdifferential with respect to a set of mult
Externí odkaz:
http://arxiv.org/abs/2307.15389
Publikováno v:
In Applied Numerical Mathematics July 2024 201:187-216
Autor:
Liu, Liya, Qin, Xiaolong
Publikováno v:
In Computers and Mathematics with Applications 1 June 2024 163:117-135
Autor:
Tan, Bing, Qin, Xiaolong
We investigate an inertial viscosity-type Tseng's extragradient algorithm with a new step size to solve pseudomonotone variational inequality problems in real Hilbert spaces. A strong convergence theorem of the algorithm is obtained without the prior
Externí odkaz:
http://arxiv.org/abs/2007.11761
Publikováno v:
Fixed Point Theory. 2022, 23(2), 707-728
The paper investigates two inertial extragradient algorithms for seeking a common solution to a variational inequality problem involving a monotone and Lipschitz continuous mapping and a fixed point problem with a demicontractive mapping in real Hilb
Externí odkaz:
http://arxiv.org/abs/2007.02746
Publikováno v:
Advances in Operator Theory. 2021, 6(4), Article ID 61
The objective of this research is to explore a convex feasibility problem, which consists of a monotone variational inequality problem and a fixed point problem. We introduce four inertial extragradient algorithms that are motivated by the inertial m
Externí odkaz:
http://arxiv.org/abs/2006.16615
Publikováno v:
Journal of Applied Analysis and Computation. 10(5), 2184-2197(2020)
In this paper, based on inertial and Tseng's ideas, we propose two projection-based algorithms to solve a monotone inclusion problem in infinite dimensional Hilbert spaces. Solution theorems of strong convergence are obtained under the certain condit
Externí odkaz:
http://arxiv.org/abs/2004.04326
Autor:
Jiang, Kai, Qin, XiaoLong
Reinforcement learning usually uses the feedback rewards of environmental to train agents. But the rewards in the actual environment are sparse, and even some environments will not rewards. Most of the current methods are difficult to get good perfor
Externí odkaz:
http://arxiv.org/abs/2001.00127