English
Related papers

Related papers: Decomposition of the NVALUE constraint

200 papers

Bessiere et al. (AAAI'08) showed that several intractable global constraints can be efficiently propagated when certain natural problem parameters are small. In particular, the complete propagation of a global constraint is fixed-parameter…

Artificial Intelligence · Computer Science 2011-04-14 Serge Gaspers , Stefan Szeider

In this work, we are concerned with a nonlinear wave equation with variable exponents. A distributive delay is imposed into the damping term with variable exponents nonlinearity. Firstly, we show that the global nonexistence time can be…

Analysis of PDEs · Mathematics 2024-11-26 Mohammad Kafini

We prove global well-posedness for the defocusing cubic wave equation with data in $H^{s} \times H^{s-1}$, $1>s>{13/18}$. The main task is to estimate the variation of an almost conserved quantity on an arbitrary long time interval. We…

Analysis of PDEs · Mathematics 2017-06-19 Tristan Roy

We describe decomposition during search (DDS), an integration of And/Or tree search into propagation-based constraint solvers. The presented search algorithm dynamically decomposes sub-problems of a constraint satisfaction problem into…

Artificial Intelligence · Computer Science 2008-06-11 Martin Mann , Guido Tack , Sebastian Will

Wavelet decompositions of integral operators have proven their efficiency in reducing computing times for many problems, ranging from the simulation of waves or fluids to the resolution of inverse problems in imaging. Unfortunately,…

Image and Video Processing · Electrical Eng. & Systems 2020-08-03 Paul Escande , Pierre Weiss

We revisit the SeqBin constraint. This meta-constraint subsumes a number of important global constraints like Change, Smooth and IncreasingNValue. We show that the previously proposed filtering algorithm for SeqBin has two drawbacks even…

Artificial Intelligence · Computer Science 2015-03-20 George Katsirelos , Nina Narodytska , Toby Walsh

With the recent success of representation learning methods, which includes deep learning as a special case, there has been considerable interest in developing representation learning techniques that can incorporate known physical…

Machine Learning · Computer Science 2021-09-10 Harsha Vardhan Tetali , Joel B. Harley , Benjamin D. Haeffele

In a distributed information application an encoder compresses an arbitrary vector while a similar reference vector is available to the decoder as side information. For the Hamming-distance similarity measure, and when guaranteed perfect…

Information Theory · Computer Science 2020-09-08 Yuval Cassuto , Jacob Ziv

Modern program verifiers use logic-based encodings of the verification problem that are discharged by a back end reasoning engine. However, instances of such encodings for large programs can quickly overwhelm these back end solvers. Hence,…

Logic in Computer Science · Computer Science 2016-07-18 Peter Schrammel

A recent body of work has demonstrated that Transformer embeddings can be linearly decomposed into well-defined sums of factors, that can in turn be related to specific network inputs or components. There is however still a dearth of work…

Computation and Language · Computer Science 2023-10-12 Timothee Mickus , Raúl Vázquez

We consider the decomposition of bounded linear operators on Hilbert spaces in terms of functions forming frames. Similar to the singular-value decomposition, the resulting frame decompositions encode information on the structure and…

Numerical Analysis · Mathematics 2021-05-26 Simon Hubmer , Ronny Ramlau

Global constraints proved themselves to be an efficient tool for modelling and solving large-scale real-life combinatorial problems. They encapsulate a set of binary constraints and using global reasoning about this set they filter the…

Programming Languages · Computer Science 2007-05-23 Roman Bartak

The challenge of learning disentangled representation has recently attracted much attention and boils down to a competition using a new real world disentanglement dataset (Gondal et al., 2019). Various methods based on variational…

Machine Learning · Computer Science 2019-12-03 Jie Qiao , Zijian Li , Boyan Xu , Ruichu Cai , Kun Zhang

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and they have been studied for many decades.…

Optimization and Control · Mathematics 2023-10-02 Levent Tunçel , Stephen A. Vavasis , Jingye Xu

In Constraint Programming, global constraints allow to model and solve many combinatorial problems. Among these constraints, several sortedness constraints have been defined, for which propagation algorithms are available, but for which the…

Computational Complexity · Computer Science 2015-06-09 Irena Rusu

Dey and Xin (J.Appl.Comput.Top., 2022, arXiv:1904.03766) describe an algorithm to decompose finitely presented multiparameter persistence modules using a matrix reduction algorithm. Their algorithm only works for modules whose generators…

Representation Theory · Mathematics 2025-11-25 Tamal K. Dey , Jan Jendrysiak , Michael Kerber

The decomposition of the linear-order metric perturbation is discussed in the context of the higher-order gauge-invariant perturbation theory. We show that the linear order metric perturbation is decomposed into gauge-invariant and…

General Relativity and Quantum Cosmology · Physics 2011-01-10 Kouji Nakamura

We propose Range and Roots which are two common patterns useful for specifying a wide range of counting and occurrence constraints. We design specialised propagation algorithms for these two patterns. Counting and occurrence constraints…

Artificial Intelligence · Computer Science 2009-03-03 Christian Bessiere , Emmanuel Hebrard , Brahim Hnich , Zeynep Kiziltan , Toby Walsh

Assessing the validity of a real-world system with respect to given quality criteria is a common yet costly task in industrial applications due to the vast number of required real-world tests. Validating such systems by means of simulation…

Machine Learning · Computer Science 2024-09-06 David Reeb , Kanil Patel , Karim Barsim , Martin Schiegg , Sebastian Gerwinn

Recent years have seen growing interest in learning disentangled representations, in which distinct features, such as size or shape, are represented by distinct neurons. Quantifying the extent to which a given representation is disentangled…

Machine Learning · Computer Science 2023-04-06 Louis Mahon , Lei Shah , Thomas Lukasiewicz