Convergence Rate Analysis of Viscosity Approximation based Gradient Algorithms

Proximal Algorithms are known to be popular in solving non-smooth convex loss minimization framework due to their low iteration costs and good performance. Convergence rate analysis is an essential part in the process of designing new proximal methods. In this paper, we present a viscosity-approxima...

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Vydané v:	Proceedings of ... International Joint Conference on Neural Networks s. 1 - 6
Hlavní autori:	Jain, Prayas, Verma, Mridula, Shukla, K.K
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.07.2020
Predmet:	Acceleration Approximation algorithms Benchmark testing Convergence Machine learning Minimization Viscosity
ISSN:	2161-4407
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