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Detectability of failures of linear programming (LP) decoding and the potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the underlying LP problem. In this paper, we…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi , Paul H. Siegel

In a recent paper [TMP, 200:1 (2019), 966--984] by the authors, a series of integrable discrete autonomous equations on a square lattice with a non-standard structure of generalized symmetries is constructed. We build modified series by…

Exactly Solvable and Integrable Systems · Physics 2020-12-02 R. N. Garifullin , R. I. Yamilov

This work builds on an existing model of discrete canonical evolution and applies it to the general case of a linear dynamical system, i.e., a finite-dimensional system with configuration space isomorphic to $ \mathbb{R}^{q} $ and linear…

Mathematical Physics · Physics 2021-06-30 Jakub Káninský

Detectability of failures of linear programming (LP) decoding and its potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the LP problem. In this paper, we make a…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi N. , Paul H. Siegel

The strengthening of linear relaxations and bounds of mixed integer linear programs has been an active research topic for decades. Enumeration-based methods for integer programming like linear programming-based branch-and-bound exploit…

Optimization and Control · Mathematics 2023-03-29 François Lamothe , Alain Haït , Emmanuel Rachelson , Claudio Contardo , Bernard Gendron

Linear constraints are the linear counterpart of Haskell's class constraints. Linearly typed parameters allow the programmer to control resources such as file handles and manually managed memory as linear arguments. Indeed, a linear type…

Programming Languages · Computer Science 2026-04-24 Arnaud Spiwack , Csongor Kiss , Jean-Philippe Bernardy , Nicolas Wu , Richard A. Eisenberg

The machine learning community has recently put effort into quantized or low-precision arithmetics to scale large models. This paper proposes performing probabilistic inference in the quantized, discrete parameter space created by these…

Machine Learning · Computer Science 2025-08-20 Aleksanteri Sladek , Martin Trapp , Arno Solin

We address the problem of complementing higher-order patterns without repetitions of existential variables. Differently from the first-order case, the complement of a pattern cannot, in general, be described by a pattern, or even by a…

Logic in Computer Science · Computer Science 2008-10-22 Alberto Momigliano , Frank Pfenning

Linear complementarity problems provide a powerful framework to model nonsmooth phenomena in a variety of real-world applications. In dynamical control systems, they appear coupled to a linear input-output system in the form of linear…

Systems and Control · Electrical Eng. & Systems 2023-03-23 Felix Miranda-Villatoro , Fernando Castaños , Alessio Franci

We use methods from algebra and discrete geometry to study the irreducibility of the dispersion polynomial of a discrete periodic operator associated to a periodic graph after changing the period lattice. We provide numerous applications of…

Algebraic Geometry · Mathematics 2024-11-12 Matthew Faust , Jordy Lopez Garcia

Localized patterns are coherent structures embedded in a quiescent state and occur in both discrete and continuous media across a wide range of applications. While it is well-understood how domain covering patterns (for example stripes and…

Pattern Formation and Solitons · Physics 2025-03-19 Jason J. Bramburger , Dan J. Hill , David J. B. Lloyd

Generalized power asymptotic expansions of solutions to differential equations that depend on parameters are investigated. The changing nature of these expansions as the parameters of the model cross critical values is discussed. An…

Classical Analysis and ODEs · Mathematics 2007-05-23 Alejandro S. Jakubi

Statistical learning in high-dimensional spaces is challenging without a strong underlying data structure. Recent advances with foundational models suggest that text and image data contain such hidden structures, which help mitigate the…

Machine Learning · Statistics 2025-02-04 Charles Arnal , Clement Berenfeld , Simon Rosenberg , Vivien Cabannes

This paper is part of a series of papers in which the asymptotic theory and appropriate symbolic computer code are developed to compute the asymptotic expansion of the solution of an n-th order ordinary differential equation. The paper…

Spectral Theory · Mathematics 2025-10-20 B. M. Brown , M. S. P. Eastham , D. K. R. McCormack

Nonparametric extension of tensor regression is proposed. Nonlinearity in a high-dimensional tensor space is broken into simple local functions by incorporating low-rank tensor decomposition. Compared to naive nonparametric approaches, our…

Machine Learning · Statistics 2016-03-09 Masaaki Imaizumi , Kohei Hayashi

Wilson lines, being comparators that render non-local operator products gauge invariant, are extensively used in QCD calculations, especially in small-$x$ calculations, calculations concerning validation of factorisation schemes and in…

High Energy Physics - Phenomenology · Physics 2015-02-03 Frederik F. Van der Veken

A foundational question in the theory of linear compartmental models is how to assess whether a model is structurally identifiable -- that is, whether parameter values can be inferred from noiseless data -- directly from the combinatorics…

Dynamical Systems · Mathematics 2024-02-19 Cashous Bortner , Elizabeth Gross , Nicolette Meshkat , Anne Shiu , Seth Sullivant

In this paper we present a nonparametric method for extending functional regression methodology to the situation where more than one functional covariate is used to predict a functional response. Borrowing the idea from Kadri et al.…

Machine Learning · Statistics 2013-01-16 Hachem Kadri , Philippe Preux , Emmanuel Duflos , Stéphane Canu

Finding patterns in graphs is a fundamental problem in databases and data mining. In many applications, graphs are temporal and evolve over time, so we are interested in finding durable patterns, such as triangles and paths, which persist…

Databases · Computer Science 2024-03-26 Pankaj K. Agarwal , Xiao Hu , Stavros Sintos , Jun Yang

The monadic shallow linear Horn fragment is well-known to be decidable and has many application, e.g., in security protocol analysis, tree automata, or abstraction refinement. It was a long standing open problem how to extend the fragment…

Logic in Computer Science · Computer Science 2017-05-25 Andreas Teucke , Christoph Weidenbach