Adaptive Projected Subgradient Method for Asymptotic Minimization of Sequence of Nonnegative Convex Functions

By Isao Yamada, Nobuhiko Ogura. 2005

195 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/befc87ff32c29fbb4a5b3606bfdc0b8e0a4eaff2

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In Civil and Structural Engineering

In Computational Mechanics

Citations in the corpus

Hybrid Steepest Descent Method for Variational Inequality Problem over the Fixed Point Set of Certain Quasi-nonexpansive Mappings (2005, methodology): “( 2002a ), Yamada ( 2003 ), Yamada and Ogura ( 2003a 2003b 2004a 2004b ), the subgradient projection was used to elude from the load for solving large scale systems of equations in an adaptive signal processing problem.”
Weak and Strong Convergence of Algorithms for the Split Common Null Point Problem (2011, methodology): “The term firmly quasi-nonexpansive (FQNE) for T class operators was used by Yamada and Ogura [44] because every firmly nonexpansive (FNE) mapping [27, page 42] is obviously FQNE.”
Diffusion Least-Mean Squares With Adaptive Combiners: Formulation and Performance Analysis (2010, methodology): “We apply a similar technique introduced in [24, Example 5].”
The Adaptive Projected Subgradient Method over the Fixed Point Set of Strongly Attracting Nonexpansive Mappings (2006, methodology): “Similar to the discussion in [36] and given the above objectives ( n)n≥0, the APSM in (3.”
Robust Distributed Estimation by Networked Agents (2017, methodology): “In [16], a robust diffusion estimation algorithm is realized by using the adaptive projected subgradient method [17], [18], culminating in a combine-project-adapt protocol, where the output errors at each node are projected onto halfspaces defined by Huber’s M-estimate error function [19].”
The Split Common Null Point Problem (2011, methodology): “ators [13]. This class coincides with the class Fν for ν = 1 [26] and with the class DC p for p= −1 [33]. The term ﬁrmly quasi-nonexpansive (FQNE) for T - class operators was used by Yamada and Ogura [44] because every ﬁrmly nonexpansive (FNE) mapping [27, page 42] is obviously FQNE. Deﬁnition 2.6 L”
Inertial Iterative Process for Fixed Points of Certain Quasi-nonexpansive Mappings (2007, background): “Recently, a successive approximation scheme was developed for finding fixed points of certain quasi-nonexpansive mappings [3, 19 ] with successful applications to image recovery problem [8].”