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Related papers: Catching the k-NAESAT Threshold

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We consider the random $k$-SAT problem with $n$ variables, $m=m(n)$ clauses, and clause density $\alpha=\lim_{n\to\infty}m/n$ for $k=2,3$. It is known that if $\alpha$ is small enough, then the random $k$-SAT problem admits a solution with…

Probability · Mathematics 2025-04-17 Andreas Basse-O'Connor , Tobias Lindhardt Overgaard , Mette Skjøtt

We investigate the clustering transition undergone by an exemplary random constraint satisfaction problem, the bicoloring of $k$-uniform random hypergraphs, when its solutions are weighted non-uniformly, with a soft interaction between…

Disordered Systems and Neural Networks · Physics 2020-11-13 Louise Budzynski , Guilhem Semerjian

An important result in discrepancy due to Banaszczyk states that for any set of $n$ vectors in $\mathbb{R}^m$ of $\ell_2$ norm at most $1$ and any convex body $K$ in $\mathbb{R}^m$ of Gaussian measure at least half, there exists a $\pm 1$…

Data Structures and Algorithms · Computer Science 2017-08-04 Nikhil Bansal , Daniel Dadush , Shashwat Garg , Shachar Lovett

We consider chains of random constraint satisfaction models that are spatially coupled across a finite window along the chain direction. We investigate their phase diagram at zero temperature using the survey propagation formalism and the…

Computational Complexity · Computer Science 2015-06-03 S. Hamed Hassani , Nicolas Macris , Rudiger Urbanke

The promise constraint satisfaction problem (PCSP) is a recently introduced vast generalisation of the constraint satisfaction problem (CSP) that captures approximability of satisfiable instances. A PCSP instance comes with two forms of…

Computational Complexity · Computer Science 2023-01-31 Alex Brandts , Stanislav Živný

An active topic in the study of random constraint satisfaction problems (CSPs) is the geometry of the space of satisfying or almost satisfying assignments as the function of the density, for which a precise landscape of predictions has been…

Data Structures and Algorithms · Computer Science 2021-06-25 Jun-Ting Hsieh , Sidhanth Mohanty , Jeff Xu

In order to obtain an evolution system which is robust against the violation of constraints, we present a new set of evolution systems based on the so-called Baumgarte-Shapiro-Shibata-Nakamura (BSSN) equations.The idea is to add functional…

General Relativity and Quantum Cosmology · Physics 2015-05-30 Takuya Tsuchiya , Gen Yoneda , Hisa-aki Shinkai

The moment measure problem consists in finding a convex function $\psi$ whose moment measure, i.e., the pushforward by $\nabla \psi$ of the measure with density $e^{-\psi(\,\cdot\,)}$, is prescribed. It is highly non-linear and less…

Functional Analysis · Mathematics 2026-04-14 Guillaume Bonnet , Yanir A. Rubinstein

The subset sum problem is known to be an NP-hard problem in the field of computer science with the fastest known approach having a run-time complexity of $O(2^{0.3113n})$. A modified version of this problem is known as the perfect sum…

Data Structures and Algorithms · Computer Science 2022-11-29 Kristof Pusztai

The Random K-Satisfiability Problem, consisting in verifying the existence of an assignment of N Boolean variables that satisfy a set of M=alpha N random logical clauses containing K variables each, is studied using the replica symmetric…

Disordered Systems and Neural Networks · Physics 2009-10-28 R. Monasson , R. Zecchina

This thesis is divided in two parts. The first presents an overview of known results in statistical mechanics of disordered systems and its approach to random combinatorial optimization problems. The second part is a discussion of two…

Statistical Mechanics · Physics 2008-01-21 Fabrizio Altarelli

Chance-constrained problems involve stochastic components in the constraints which can be violated with a small probability. We investigate the impact of different types of chance constraints on the performance of iterative search…

Neural and Evolutionary Computing · Computer Science 2024-05-30 Saba Sadeghi Ahouei , Jacob de Nobel , Aneta Neumann , Thomas Bäck , Frank Neumann

We study sample average approximations (SAA) of chance constrained programs. SAA methods typically approximate the actual distribution in the chance constraint using an empirical distribution constructed from random samples assumed to be…

Optimization and Control · Mathematics 2022-05-13 Shuhao Yan , Francesca Parise , Eilyan Bitar

We study the consistency of the $k$-nearest neighbor regressor under complex survey designs. While consistency results for this algorithm are well established for independent and identically distributed data, corresponding results for…

Machine Learning · Statistics 2026-03-19 Caren Hasler

In this paper, we present approximation algorithms for combinatorial optimization problems under probabilistic constraints. Specifically, we focus on stochastic variants of two important combinatorial optimization problems: the k-center…

Data Structures and Algorithms · Computer Science 2008-09-03 Shipra Agrawal , Amin Saberi , Yinyu Ye

A major problem in evaluating stochastic local search algorithms for NP-complete problems is the need for a systematic generation of hard test instances having previously known properties of the optimal solutions. On the basis of…

Disordered Systems and Neural Networks · Physics 2009-11-07 W. Barthel , A. K. Hartmann , M. Leone , F. Ricci-Tersenghi , M. Weigt , R. Zecchina

We study the structure of satisfying assignments of a random 3-SAT formula. In particular, we show that a random formula of density 4.453 or higher almost surely has no non-trivial "core" assignments. Core assignments are certain partial…

Computational Complexity · Computer Science 2008-09-01 Elitza Maneva , Alistair Sinclair

Constraint satisfaction problems have been studied in numerous fields with practical and theoretical interests. In recent years, major breakthroughs have been made in a study of counting constraint satisfaction problems (or #CSPs). In…

Computational Complexity · Computer Science 2012-10-23 Tomoyuki Yamakami

We analyse the performance of Belief Propagation Guided Decimation, a physics-inspired message passing algorithm, on the random $k$-XORSAT problem. Specifically, we derive an explicit threshold up to which the algorithm succeeds with a…

Combinatorics · Mathematics 2025-09-03 Arnab Chatterjee , Amin Coja-Oghlan , Mihyun Kang , Lena Krieg , Maurice Rolvien , Gregory B. Sorkin

We study the statistical mechanics of a class of problems whose phase space is the set of permutations of an ensemble of quenched random positions. Specific examples analyzed are the finite temperature traveling salesman problem on several…

Disordered Systems and Neural Networks · Physics 2009-11-11 David S. Dean , David Lancaster , Satya. N. Majumdar