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Some of the most important results in prediction theory and time series analysis when finitely many values are removed from or added to its infinite past have been obtained using difficult and diverse techniques ranging from duality in…

Probability · Mathematics 2007-08-30 Yukio Kasahara , Mohsen Pourahmadi , Akihiko Inoue

Our first result is a statement of a somewhat general form of a non-substitution theorem for linear programming problems, along with a very easy proof of the same. Subsequently, we provide an easy proof of theorem 1 in a 1979 paper of Olvi…

Optimization and Control · Mathematics 2025-04-08 Somdeb Lahiri

An infinite set is orbit-finite if, up to permutations of the underlying structure of atoms, it has only finitely many elements. We study a generalisation of linear programming where constraints are expressed by an orbit-finite system of…

Logic in Computer Science · Computer Science 2024-11-14 Arka Ghosh , Piotr Hofman , Sławomir Lasota

Lie's linearizability criteria for scalar second-order ordinary differential equations had been extended to systems of second-order ordinary differential equations by using geometric methods. These methods not only yield the linearizing…

Classical Analysis and ODEs · Mathematics 2011-07-25 S. Ali , F. M. Mahomed , Asghar Qadir

We consider linear programming (LP) problems in infinite dimensional spaces that are in general computationally intractable. Under suitable assumptions, we develop an approximation bridge from the infinite-dimensional LP to tractable finite…

Optimization and Control · Mathematics 2017-02-22 Peyman Mohajerin Esfahani , Tobias Sutter , Daniel Kuhn , John Lygeros

Matrix completion aims to predict missing elements in a partially observed data matrix which in typical applications, such as collaborative filtering, is large and extremely sparsely observed. A standard solution is matrix factorization,…

Machine Learning · Computer Science 2019-08-06 Xiangju Qin , Paul Blomstedt , Samuel Kaski

This paper revisits the well-studied fixed point problem from a unified viewpoint of mathematical modeling and canonical duality theory, i.e. the original problem is first reformulated as a nonconvex optimization problem, its well-posedness…

Optimization and Control · Mathematics 2018-01-29 Ning Ruan , David Yang Gao

Causal inference is known to be very challenging when only observational data are available. Randomized experiments are often costly and impractical and in instrumental variable regression the number of instruments has to exceed the number…

Methodology · Statistics 2018-06-19 Dominik Rothenhäusler , Peter Bühlmann , Nicolai Meinshausen

How can complexity theory and algorithms benefit from practical advances in computing? We give a short overview of some prior work using practical computing to attack problems in computational complexity and algorithms, informally describe…

Computational Complexity · Computer Science 2008-11-11 Ryan Williams

Given samples of a real or complex-valued function on a set of distinct nodes, the traditional linear Chebyshev approximation is to compute the best minimax approximation on a prescribed linear functional space. Lawson's iteration is a…

Numerical Analysis · Mathematics 2023-08-16 Linyi Yang , Lei-Hong Zhang , Ya-Nan Zhang

The importance of transformations and normal forms in logic programming, and generally in computer science, is well documented. This paper investigates transformations and normal forms in the context of Defeasible Logic, a simple but…

Logic in Computer Science · Computer Science 2021-02-16 G. Antoniou , D. Billington , G. Governatori , M. J. Maher

To reduce human error and prejudice, many high-stakes decisions have been turned over to machine algorithms. However, recent research suggests that this does not remove discrimination, and can perpetuate harmful stereotypes. While…

Computers and Society · Computer Science 2019-12-18 Yuzi He , Keith Burghardt , Kristina Lerman

Derivative-based algorithms are ubiquitous in statistics, machine learning, and applied mathematics. Automatic differentiation offers an algorithmic way to efficiently evaluate these derivatives from computer programs that execute relevant…

Computation · Statistics 2022-03-01 Charles C. Margossian , Michael Betancourt

When Fourier series are employed to solve partial differential equations, low-pass filters can be used to regularize divergent series that may appear. In this paper we show that the linear low-pass filters defined in a previous paper can be…

Complex Variables · Mathematics 2015-03-25 Jorge L. deLyra

The notion of symmetry is defined in the context of Linear and Integer Programming. Symmetric linear and integer programs are studied from a group theoretical viewpoint. We show that for any linear program there exists an optimal solution…

Combinatorics · Mathematics 2009-08-25 R. Bödi , K. Herr

Gaussian elimination (GE) is the archetypal direct algorithm for solving linear systems of equations and this has been its primary application for thousands of years. In the last decade, GE has found another major use as an iterative…

Numerical Analysis · Mathematics 2016-02-23 Alex Townsend

We discuss the effective computation of geometric singularities of implicit ordinary differential equations over the real numbers using methods from logic. Via the Vessiot theory of differential equations, geometric singularities can be…

Logic · Mathematics 2021-07-06 Werner M. Seiler , Matthias Seiss , Thomas Sturm

A fundamental problem in program verification concerns the termination of simple linear loops of the form x := u ; while Bx >= b do {x := Ax + a} where x is a vector of variables, u, a, and c are integer vectors, and A and B are integer…

Computational Complexity · Computer Science 2014-10-14 Joël Ouaknine , João Sousa Pinto , James Worrell

We argue that the variational calculus leading to Euler's equations and Noether's theorem can be replaced by equivariance and invariance conditions avoiding the action integral. We also speculate about the origin of Lagrangian theories in…

Mathematical Physics · Physics 2008-04-25 George Svetlichny

In this paper, we propose two algorithms for solving linear inverse problems when the observations are corrupted by noise. A proper data fidelity term (log-likelihood) is introduced to reflect the statistics of the noise (e.g. Gaussian,…

Applications · Statistics 2011-03-14 François-Xavier Dupé , Jalal Fadili , Jean-Luc Starck