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The Kaczmarz algorithm is an iterative method to reconstruct an unknown vector $f$ from inner products $\langle f , \varphi_{n} \rangle $. We consider the problem of how additive noise affects the reconstruction under the assumption that…

Functional Analysis · Mathematics 2019-06-21 Caleb Camrud , Evan Camrud , Lee Przybylski , Eric S. Weber

Some observational constraints on the brane-world based on predictions from specific models in five dimensions, have been recently reported, both on local and cosmological scales. In order to identify the origins of these constraints, the…

Astrophysics · Physics 2007-05-23 M. D. Maia , E. M. Monte

In this report, we propose a quick survey of the currently known techniques for encoding a Boolean cardinality constraint into a CNF formula, and we discuss about the relevance of these encodings. We also propose models to facilitate…

Artificial Intelligence · Computer Science 2010-12-20 Olivier Bailleux

To predict allowable time-step size for the fully discretized nonlinear differential equations, a stability theory is developed using exact determination of an infinite perturbation series. Mathematical induction is used to determine the…

Numerical Analysis · Mathematics 2013-11-05 Arash Ghasemi , Kidambi Sreenivas , Lafayette K. Taylor

Many interesting problems in fields ranging from telecommunications to computational biology can be formalized in terms of large underdetermined systems of linear equations with additional constraints or regularizers. One of the most…

Machine Learning · Statistics 2019-08-06 Alfredo Braunstein , Anna Paola Muntoni , Andrea Pagnani , Mirko Pieropan

In machine learning, it is commonly assumed that training and test data share the same population distribution. However, this assumption is often violated in practice because the sample selection bias may induce the distribution shift from…

Machine Learning · Computer Science 2020-06-09 Kun Kuang , Hengtao Zhang , Fei Wu , Yueting Zhuang , Aijun Zhang

Scalar auxiliary variable (SAV) methods are a class of linear schemes for solving gradient flows that are known for the stability of a `modified' energy. In this paper, we propose an improved SAV (iSAV) scheme that not only retains the…

Numerical Analysis · Mathematics 2024-05-14 RUi Chen , Tingfeng Wang , Xiaofei Zhao

We study the stability with respect to perturbations and the accuracy of numerical algorithms for computing solutions to the multilinear PageRank problem $\mathbf{x} = (1-\alpha)\mathbf{v} + \alpha \mathcal{P} \mathbf{x}^2$. Our results…

Numerical Analysis · Mathematics 2025-06-24 Mehdi Najafi Kalyani , Federico Poloni

The recent measurements of the Cosmic Microwave Background anisotropies at arcminute angular scales performed by the ACT and SPT experiments are probing the damping regime of CMB fluctuations. The analysis of these datasets unexpectedly…

Cosmology and Nongalactic Astrophysics · Physics 2013-05-30 Eloisa Menegoni , Maria Archidiacono , Erminia Calabrese , Silvia Galli , C. J. A. P. Martins , Alessandro Melchiorri

This paper presents a systematic method for synthesizing a Control Barrier Function (CBF) that encodes predictive information into a CBF. Unlike other methods, the synthesized CBF can account for changes and time-variations in the…

Systems and Control · Electrical Eng. & Systems 2025-04-23 Adrian Wiltz , Dimos V. Dimarogonas

The linear fractional stable motion (LFSM) extends the fractional Brownian motion (fBm) by considering $\alpha$-stable increments. We propose a method to forecast future increments of the LFSM from past discrete-time observations, using the…

Methodology · Statistics 2026-05-12 Matthieu Garcin , Karl Sawaya , Thomas Valade

Counterfactual explanations (CFEs) exemplify how to minimally modify a feature vector to achieve a different prediction for an instance. CFEs can enhance informational fairness and trustworthiness, and provide suggestions for users who…

Machine Learning · Computer Science 2023-09-12 Yongjie Wang , Hangwei Qian , Yongjie Liu , Wei Guo , Chunyan Miao

A Constraint Satisfaction Problem (CSP) is a framework used for modeling and solving constrained problems. Tree-search algorithms like backtracking try to construct a solution to a CSP by selecting the variables of the problem one after…

Artificial Intelligence · Computer Science 2014-10-06 Muhammad Rezaul Karim

Extracting parameter constraints from cosmological observations requires accurate determination of the covariance matrix for use in the likelihood function. We show here that uncertainties in the elements of the covariance matrix propagate…

Cosmology and Nongalactic Astrophysics · Physics 2013-10-30 Scott Dodelson , Michael D. Schneider

In 2007 it was conjectured that the Constraint Satisfaction Problem (CSP) over a constraint language $\Gamma$ is tractable if and only if $\Gamma$ is preserved by a weak near-unanimity (WNU) operation. After many efforts and partial…

Computational Complexity · Computer Science 2020-05-05 Dmitriy Zhuk

This paper is devoted to the stability analysis of a classical three-field formulation of Biot's consolidation model where the unknown variables are the displacements, fluid flux (Darcy velocity), and pore pressure. Specific…

Numerical Analysis · Mathematics 2018-06-21 Qingguo Hong , Johannes Kraus

A CSP with n variables ranging over a domain of d values can be solved by brute-force in d^n steps (omitting a polynomial factor). With a more careful approach, this trivial upper bound can be improved for certain natural restrictions of…

Computational Complexity · Computer Science 2013-04-09 Iyad Kanj , Stefan Szeider

We review recent efforts to re-formulate the Einstein equations for fully relativistic numerical simulations. In order to complete a long-term and accurate simulations of binary compact objects, people seek a robust set of equations against…

General Relativity and Quantum Cosmology · Physics 2010-11-02 Hisa-aki Shinkai

The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving problems involving both hard constraints and cost functions. It has been applied to various problems, including resource allocation,…

Artificial Intelligence · Computer Science 2014-01-16 Matthias Zytnicki , Christine Gaspin , Simon de Givry , Thomas Schiex

We propose a new numerical technique to deal with nonlinear terms in gradient flows. By introducing a scalar auxiliary variable (SAV), we construct efficient and robust energy stable schemes for a large class of gradient flows. The SAV…

Numerical Analysis · Mathematics 2017-10-05 Jie Shen , Jie Xu , Jiang Yang