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CSP sparsification, introduced by Kogan and Krauthgamer (ITCS 2015), considers the following question: how much can an instance of a constraint satisfaction problem be sparsified (by retaining a reweighted subset of the constraints) while…

Data Structures and Algorithms · Computer Science 2024-11-07 Sanjeev Khanna , Aaron L. Putterman , Madhu Sudan

Schaefer's dichotomy theorem [Schaefer, STOC'78] states that a boolean constraint satisfaction problem (CSP) is polynomial-time solvable if one of six given conditions holds for every type of constraint allowed in its instances. Otherwise,…

Computational Complexity · Computer Science 2023-07-10 Patrick Schnider , Simon Weber

We show that for every $k\in\mathbb{N}$ and $\varepsilon>0$, for large enough alphabet $R$, given a $k$-CSP with alphabet size $R$, it is NP-hard to distinguish between the case that there is an assignment satisfying at least…

Computational Complexity · Computer Science 2025-10-29 Dor Minzer , Kai Zhe Zheng

The estimation of phase transitions in random boolean Constraint Satisfaction Problems (CSP) is based on two fundamental tools: the first and second moment methods. While the first moment method on the number of solutions permits to compute…

Discrete Mathematics · Computer Science 2011-09-27 Yacine Boufkhad , Olivier Dubois

This paper is our third step towards developing a theory of testing monomials in multivariate polynomials and concentrates on two problems: (1) How to compute the coefficients of multilinear monomials; and (2) how to find a maximum…

Computational Complexity · Computer Science 2015-05-19 Zhixiang Chen , Bin Fu

We initiate a study of the streaming complexity of constraint satisfaction problems (CSPs) when the constraints arrive in a random order. We show that there exists a CSP, namely $\textsf{Max-DICUT}$, for which random ordering makes a…

Data Structures and Algorithms · Computer Science 2023-04-14 Raghuvansh R. Saxena , Noah Singer , Madhu Sudan , Santhoshini Velusamy

This paper gives a dichotomy theorem for the complexity of computing the partition function of an instance of a weighted Boolean constraint satisfaction problem. The problem is parameterised by a finite set F of non-negative functions that…

Computational Complexity · Computer Science 2009-02-23 Martin Dyer , Leslie Ann Goldberg , Mark Jerrum

A fundamental problem in numerical analysis and approximation theory is approximating smooth functions by polynomials. A much harder version under recent consideration is to enforce bounds constraints on the approximating polynomial. In…

Numerical Analysis · Mathematics 2021-12-28 Larry Allen , Robert C. Kirby

The Constraint Satisfaction Problem (CSP) is a problem of computing a homomorphism $\mathbf{R}\to \mathbf{\Gamma}$ between two relational structures, where $\mathbf{R}$ is defined over a domain $V$ and $\mathbf{\Gamma}$ is defined over a…

Computational Complexity · Computer Science 2023-11-21 Rustem Takhanov

We give a {\em deterministic} algorithm for approximately computing the fraction of Boolean assignments that satisfy a degree-$2$ polynomial threshold function. Given a degree-2 input polynomial $p(x_1,\dots,x_n)$ and a parameter $\eps >…

Computational Complexity · Computer Science 2013-11-28 Anindya De , Ilias Diakonikolas , Rocco A. Servedio

We consider the following basic problem: given an $n$-variate degree-$d$ homogeneous polynomial $f$ with real coefficients, compute a unit vector $x \in \mathbb{R}^n$ that maximizes $|f(x)|$. Besides its fundamental nature, this problem…

Data Structures and Algorithms · Computer Science 2017-04-25 Vijay Bhattiprolu , Mrinalkanti Ghosh , Venkatesan Guruswami , Euiwoong Lee , Madhur Tulsiani

Constraint satisfaction problems (CSPs) are a natural class of decision problems where one must decide whether there is an assignment to variables that satisfies a given formula. Schaefer's dichotomy theorem, and its extension to all…

Quantum Physics · Physics 2025-02-27 Eric Culf , Kieran Mastel

The purpose of this article is to examine and limit the conditions in which the P complexity class could be equivalent to the NP complexity class. Proof is provided by demonstrating that as the number of clauses in a NP-complete problem…

Computational Complexity · Computer Science 2008-09-07 Jerrald Meek

We study the complexity of the Distributed Constraint Satisfaction Problem (DCSP) on a synchronous, anonymous network from a theoretical standpoint. In this setting, variables and constraints are controlled by agents which communicate with…

Data Structures and Algorithms · Computer Science 2021-01-25 Silvia Butti , Victor Dalmau

Promise Constraint Satisfaction Problems (PCSPs) are a generalization of Constraint Satisfaction Problems (CSPs) where each predicate has a strong and a weak form and given a CSP instance, the objective is to distinguish if the strong form…

Computational Complexity · Computer Science 2023-06-22 Joshua Brakensiek , Venkatesan Guruswami , Sai Sandeep

In this thesis, we explore streaming algorithms for approximating constraint satisfaction problems (CSPs). The setup is roughly the following: A computer has limited memory space, sees a long "stream" of local constraints on a set of…

Data Structures and Algorithms · Computer Science 2023-04-14 Noah G. Singer

Boolean Satisfiability Problem (SAT) is one of the core problems in computer science. As one of the fundamental NP-complete problems, it can be used - by known reductions - to represent instances of variety of hard decision problems.…

Data Structures and Algorithms · Computer Science 2019-11-05 Michał Karpiński

We consider the problem of approximating the reachable set of a discrete-time polynomial system from a semialgebraic set of initial conditions under general semialgebraic set constraints. Assuming inclusion in a given simple set like a box…

Optimization and Control · Mathematics 2019-06-06 Victor Magron , Pierre-Loic Garoche , Didier Henrion , Xavier Thirioux

We present an efficient algorithm to solve semirandom planted instances of any Boolean constraint satisfaction problem (CSP). The semirandom model is a hybrid between worst-case and average-case input models, where the input is generated by…

Computational Complexity · Computer Science 2023-10-02 Venkatesan Guruswami , Jun-Ting Hsieh , Pravesh K. Kothari , Peter Manohar

We study the problem of approximating the value of a Unique Game instance in the streaming model. A simple count of the number of constraints divided by $p$, the alphabet size of the Unique Game, gives a trivial $p$-approximation that can…

Computational Complexity · Computer Science 2020-11-13 Venkatesan Guruswami , Runzhou Tao
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