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This article provides an original understanding of the behavior of a class of graph-oriented semi-supervised learning algorithms in the limit of large and numerous data. It is demonstrated that the intuition at the root of these methods…

Machine Learning · Computer Science 2017-11-10 Xiaoyi Mai , Romain Couillet

The simultaneous quantum estimation of multiple parameters can provide a better precision than estimating them individually. This is an effect that is impossible classically. We review the rich background of multi-parameter quantum…

Quantum Physics · Physics 2016-09-28 Magdalena Szczykulska , Tillmann Baumgratz , Animesh Datta

Suppose data are fitted to some parametric model but that the true model happens to be one with an additional parameter. When a parameter is to be estimated one can use likelihood estimation in the wider model or in the narrow model.…

Methodology · Statistics 2026-03-27 Nils Lid Hjort

Spectral methods are now common in the solution of ordinary differential eigenvalue problems in a wide variety of fields, such as in the computation of black hole quasinormal modes. Most of these spectral codes are based on standard…

General Relativity and Quantum Cosmology · Physics 2024-01-18 Sean Fortuna , Ian Vega

We study the problem of parameter-free stochastic optimization, inquiring whether, and under what conditions, do fully parameter-free methods exist: these are methods that achieve convergence rates competitive with optimally tuned methods,…

Machine Learning · Computer Science 2024-10-22 Amit Attia , Tomer Koren

The problem of parameterization is often central to the effective deployment of nature-inspired algorithms. However, finding the optimal set of parameter values for a combination of problem instance and solution method is highly…

Neural and Evolutionary Computing · Computer Science 2014-06-26 Matthew Crossley , Andy Nisbet , Martyn Amos

The recently reported compactified hyperboloidal method has found wide use in the numerical computation of quasinormal modes, with implications for fields as diverse as gravitational physics and optics. We extend this intrinsically…

Computational Physics · Physics 2024-09-05 Christopher Burgess , Friedrich Koenig

This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [Kivinen & Warmuth, 1994]. We provide a unified framework for…

Machine Learning · Computer Science 2013-02-08 Eric Bauer , Daphne Koller , Yoram Singer

The fundamental quasinormal modes of black holes in higher-derivative gravity given by the Einstein-Weyl action are known to be moderately corrected by the Weyl term. Here we will show that the first several overtones are highly sensitive…

General Relativity and Quantum Cosmology · Physics 2023-04-14 R. A. Konoplya

Two quantum-corrected black hole models have recently been proposed within the Hamiltonian constraints approach to quantum gravity, maintaining general covariance \cite{Zhang:2024khj}. We have studied the quasinormal spectra of these black…

General Relativity and Quantum Cosmology · Physics 2025-05-28 R. A. Konoplya , O. S. Stashko

We consider quantum communication schemes where quantum optical signals are exchanged between a source on Earth and a satellite. The background curved spacetime affects the quantum state of the propagating photons. We employ…

Quantum Physics · Physics 2019-04-02 Jan Kohlrus , David Edward Bruschi , Ivette Fuentes

In this short note, we briefly comment on the analytical bounds that must be imposed on the parameter space of the Rezzolla-Zhidenko (RZ) metric-parametrization approach introduced in Ref. [1]. We hope this will clarify some of the…

General Relativity and Quantum Cosmology · Physics 2022-06-08 Prashant Kocherlakota , Luciano Rezzolla

We present an experimental and theoretical study of the effect of spatio-temporal fluctuations in quasi-reversible systems displaying a spatial quintic supercritical bifurcation. The saturation mechanism is drastically changed by the…

Pattern Formation and Solitons · Physics 2025-02-27 Marcel G. Clerc , Claudio Falcón , René G. Rojas

A common problem in data analysis is that the functional form, as well as the parameter values, of the underlying model which should describe a dataset is not known a priori. In these cases some extra uncertainty must be assigned to the…

Data Analysis, Statistics and Probability · Physics 2015-05-20 P. D. Dauncey , M. Kenzie , N. Wardle , G. J. Davies

We present an exact expression for the quasinormal modes of scalar, electromagnetic and gravitational perturbations of a near extremal Scwarzschild-de Sitter black hole and we show why a previous approximation holds exactly in this near…

General Relativity and Quantum Cosmology · Physics 2016-08-31 Vitor Cardoso , Jose' P. S. Lemos

A modification of General Relativity that is based on the gravitational Standard-Model Extension and incorporates nondynamical background fields has recently been studied via the ADM formalism. Our objective in this paper is to develop a…

General Relativity and Quantum Cosmology · Physics 2023-05-15 Carlos M. Reyes , Marco Schreck

We consider adaptive control problem in presence of nonlinear parametrization of uncertainties in the model. It is shown that despite traditional approaches require for domination in the control loop during adaptation, it is not often…

Optimization and Control · Mathematics 2007-05-23 Ivan Tyukin , Cees van Leeuwen

In this work we explore some aspects of the spectral instability of back hole quasi-normal modes, using a specific model as an example. The model is that of a small bump perturbation to the effective potential of linear axial gravitational…

General Relativity and Quantum Cosmology · Physics 2025-01-08 Valentin Boyanov

We investigate the pseudospectrum of a Schwarzschild-like spacetime within the framework of black hole perturbation theory to analyze a counterintuitive assertion regarding the instability of quasinormal modes. Recent findings suggest that…

General Relativity and Quantum Cosmology · Physics 2025-05-14 Pedro Henrique Croti Siqueira , Lucas Tobias de Paula , Rodrigo Panosso Macedo , Maurício Richartz

Many inverse problems include nuisance parameters which, while not of direct interest, are required to recover primary parameters. Structure present in these problems allows efficient optimization strategies - a well known example is…

Numerical Analysis · Mathematics 2015-06-05 Aleksandr Y. Aravkin , Tristan van Leeuwen