Asymptotic Convergence Analysis of a New Class of Proximal Point Methods

2007 ◽  
Vol 46 (5) ◽  
pp. 1683-1704 ◽  
Author(s):  
William W. Hager ◽  
Hongchao Zhang
2020 ◽  
Vol 186 (3) ◽  
pp. 879-898
Author(s):  
Erik Alex Papa Quiroz ◽  
Nancy Baygorrea Cusihuallpa ◽  
Nelson Maculan

Optimization ◽  
2019 ◽  
Vol 69 (7-8) ◽  
pp. 1655-1680 ◽  
Author(s):  
Nopparat Wairojjana ◽  
Nuttapol Pakkaranang ◽  
Izhar Uddin ◽  
Poom Kumam ◽  
Aliyu Muhammed Awwal

2009 ◽  
Vol 2009 ◽  
pp. 1-11
Author(s):  
Ram U. Verma

Based on a notion ofrelatively maximal(m)-relaxed monotonicity, the approximation solvability of a general class of inclusion problems is discussed, while generalizing Rockafellar's theorem (1976) on linear convergence using the proximal point algorithm in a real Hilbert space setting. Convergence analysis, based on this new model, is simpler and compact than that of the celebrated technique of Rockafellar in which the Lipschitz continuity at 0 of the inverse of the set-valued mapping is applied. Furthermore, it can be used to generalize the Yosida approximation, which, in turn, can be applied to first-order evolution equations as well as evolution inclusions.


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