Abstract: This paper studies the convergence of a fixed point iteration algorithm for the problem of max-min signal-to-interference ratio (SIR) balancing. Differently from the existing work on the ...
ABSTRACT: In this paper, we investigate fixed point results for Jaggi-type F-contractions in the framework of cone b-metric spaces. Motivated by the need for faster convergence in iterative methods, ...
Abstract: In this article, we use methods from fixed point theory to examine a Lambda policy iteration with a randomization algorithm mappings that satisfy the Kannan contraction condition. As shown ...
Anderson acceleration is an optimisation technique designed to improve the convergence of fixed-point iterations, a common approach utilised in solving nonlinear equations. By blending current and ...
Fixed point theory is a central topic in functional analysis that examines conditions under which a mapping in a Banach space admits points that remain invariant under the transformation. Particularly ...
If you use this code in your research, please cite our paper: @article{ terashita2025variance, title={Variance Reduction of Stochastic Hypergradient Estimation by Mixed Fixed-Point Iteration}, author= ...
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Newton's method is actually a special case of what is generally known as a fixed point method. These methods rely on the Fixed point Theorem: ...
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