This repository contains the code and experiments for the Master's thesis on preconditioning strategies for iterative methods applied to the Vecchia-Laplace approximation, developed using the GPBoost ...

Abstract: Spectrum optimization is a promising means to tackle the crosstalk problem in DSL systems, and corresponds to a challenging nonconvex optimization problem. Iterative convex approximation ...

Gradient descent (and especially its stochastic variants) is the foundational iterative optimization tool for training deep neural networks, ranging from basic feed-forward networks to complex ...

ABSTRACT: In this paper, to find the fixed points of the nonexpansive nonself-mappings, we introduced two new viscosity approximation methods, and then we prove the iterative sequences defined by ...

This chapter explains how to evaluate the implied volatility function in a computationally efficient manner for the widest range of option prices. The Black‐Scholes formula defines an invertible ...