Convergence analysis of smoothed stochastic gradient-type algorithm

1987 ◽  
Vol 18 (6) ◽  
pp. 1061-1078 ◽  
Author(s):  
NADAV BERMAN ◽  
ARIE FEUER ◽  
ELIAS WAHNON
2007 ◽  
Vol 119 (1) ◽  
pp. 51-78 ◽  
Author(s):  
Kengy Barty ◽  
Jean-Sébastien Roy ◽  
Cyrille Strugarek

Author(s):  
Jamilu Sabi'u ◽  
Abdullah Shah

In this article, we proposed two Conjugate Gradient (CG) parameters using the modified Dai-{L}iao condition and the descent three-term CG search direction. Both parameters are incorporated with the projection technique for solving large-scale monotone nonlinear equations. Using the Lipschitz and monotone assumptions, the global convergence of methods has been proved. Finally, numerical results are provided to illustrate the robustness of the proposed methods.


2019 ◽  
Vol 84 (2) ◽  
pp. 485-512 ◽  
Author(s):  
Cristian Daniel Alecsa ◽  
Szilárd Csaba László ◽  
Adrian Viorel

2020 ◽  
Vol 25 (5) ◽  
pp. 1729-1755
Author(s):  
Cristian Barbarosie ◽  
◽  
Anca-Maria Toader ◽  
Sérgio Lopes ◽  

2018 ◽  
Vol 62 (1) ◽  
Author(s):  
Changyou Chen ◽  
Wenlin Wang ◽  
Yizhe Zhang ◽  
Qinliang Su ◽  
Lawrence Carin

2008 ◽  
Vol 429 (5-6) ◽  
pp. 1229-1242 ◽  
Author(s):  
Catherine Fraikin ◽  
Yurii Nesterov ◽  
Paul Van Dooren
Keyword(s):  

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