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The purpose of this paper is twofold. First, the definition of new statistical convergence with Fibonacci sequence is given and some fundamental properties of statistical convergence are examined. Second, approximation theory worked as a…

Functional Analysis · Mathematics 2016-07-11 Murat Kirisci , Ali Karaisa

In this paper, we present a comprehensive system for the treatment of the topic of limits--conceptually, computationally, and formally. The system addresses fundamental linguistic flaws in the standard presentation of limits, which attempts…

General Mathematics · Mathematics 2007-05-23 Frank Swenton

The paper develops the stiffness relationship between the movements and forces among a system of discrete interacting grains. The approach is similar to that used in structural analysis, but the stiffness matrix of granular material is…

Soft Condensed Matter · Physics 2019-05-01 Matthew R. Kuhn , Florent Prunier , Ali Daouadji

The main focus of this work is on providing a formal definition of statistical depth for functional data on the basis of six properties, recognising topological features such as continuity, smoothness and contiguity. Amongst our depth…

Statistics Theory · Mathematics 2015-10-15 Alicia Nieto-Reyes , Heather Battey

We review the current status of dimensions, as the result of a long and controversial history that includes input from philosophy and physics. Our conclusion is that they are subjective but essential concepts which provide a kind of…

General Relativity and Quantum Cosmology · Physics 2015-05-13 Paul S. Wesson

Recently there has been a dramatic increase in the performance of recognition systems due to the introduction of deep architectures for representation learning and classification. However, the mathematical reasons for this success remain…

Machine Learning · Computer Science 2017-12-14 Rene Vidal , Joan Bruna , Raja Giryes , Stefano Soatto

Fair classification has been a topic of intense study in machine learning, and several algorithms have been proposed towards this important task. However, in a recent study, Friedler et al. observed that fair classification algorithms may…

Machine Learning · Computer Science 2020-09-10 Lingxiao Huang , Nisheeth K. Vishnoi

We extend the theory of neural fields which has been developed in a deterministic framework by considering the influence spatio-temporal noise. The outstanding problem that we here address is the development of a theory that gives rigorous…

Probability · Mathematics 2013-11-22 Olivier Faugeras , James Inglis

The quest for quantum computers is motivated by their potential for solving problems that defy existing, classical, computers. The theory of computational complexity, one of the crown jewels of computer science, provides a rigorous…

Statistical Mechanics · Physics 2010-09-10 C. R. Laumann , R. Moessner , A. Scardicchio , S. L. Sondhi

Robustness of linear systems with constant coefficients is considered. There exist methods and tools for analyzing the stability of systems with random or deterministic uncertainties. At the same time, there are no approaches for the…

Optimization and Control · Mathematics 2020-12-08 Andrey Tremba

Program specialisation aims at improving the overall performance of programs by performing source to source transformations. A common approach within functional and logic programming, known respectively as partial evaluation and partial…

Programming Languages · Computer Science 2007-05-23 Michael Leuschel , Maurice Bruynooghe

Neural networks are becoming increasingly prevalent in software, and it is therefore important to be able to verify their behavior. Because verifying the correctness of neural networks is extremely challenging, it is common to focus on the…

Machine Learning · Computer Science 2019-02-19 Ravi Mangal , Aditya V. Nori , Alessandro Orso

We commonly think of mathematics as bringing precision to application domains, but its relationship with computer science is more complex. This experience report on the use of Racket and Haskell to teach a required first university CS…

Programming Languages · Computer Science 2013-01-23 Prabhakar Ragde

This work presents an empirical analysis of exact algorithms for the unbounded knapsack problem, which includes seven algorithms from the literature, two commercial solvers, and more than ten thousand instances. The terminating step-off, a…

Data Structures and Algorithms · Computer Science 2019-03-22 Henrique Becker , Luciana S. Buriol

The notion of drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time. Albeit many attempts were made to deal with drift, formal notions of drift are application-dependent and…

Machine Learning · Computer Science 2019-12-05 Fabian Hinder , André Artelt , Barbara Hammer

Stochastic contraction analysis is a recently developed tool for studying the global stability properties of nonlinear stochastic systems, based on a differential analysis of convergence in an appropriate metric. To date, stochastic…

Optimization and Control · Mathematics 2013-04-02 Quang-Cuong Pham , Jean-Jacques Slotine

"Clarithmetic" is a generic name for formal number theories similar to Peano arithmetic, but based on computability logic (see http://www.cis.upenn.edu/~giorgi/cl.html) instead of the more traditional classical or intuitionistic logics.…

Logic in Computer Science · Computer Science 2011-08-24 Giorgi Japaridze

The notion of $1$-affineness was originally formulated by Gaitsgory in the context of derived algebraic geometry. Motivated by applications to rigid and analytic geometry, we introduce two very general and abstract frameworks where it makes…

Algebraic Geometry · Mathematics 2025-09-08 Matteo Montagnani , Emanuele Pavia

Many complex systems satisfy a set of constraints on their degrees of freedom, and at the same time, they are able to work and adapt to different conditions. Here, we describe the emergence of this ability in a simplified model in which the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Ginestra Bianconi , Roberto Mulet

Fatigue strength estimation is a costly manual material characterization process in which state-of-the-art approaches follow a standardized experiment and analysis procedure. In this paper, we examine a modular, Machine Learning-based…

Machine Learning · Computer Science 2022-12-05 Dorina Weichert , Alexander Kister , Sebastian Houben , Gunar Ernis , Stefan Wrobel