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For input $x$, let $F(x)$ denote the set of outputs that are the "legal" answers for a computational problem $F$. Suppose $x$ and members of $F(x)$ are so large that there is not time to read them in their entirety. We propose a model of…

Data Structures and Algorithms · Computer Science 2011-04-08 Ronitt Rubinfeld , Gil Tamir , Shai Vardi , Ning Xie

We show that any randomised Monte Carlo distributed algorithm for the Lov\'asz local lemma requires $\Omega(\log \log n)$ communication rounds, assuming that it finds a correct assignment with high probability. Our result holds even in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-04 Sebastian Brandt , Orr Fischer , Juho Hirvonen , Barbara Keller , Tuomo Lempiäinen , Joel Rybicki , Jukka Suomela , Jara Uitto

The constructive Lov\'{a}sz Local Lemma has become a central tool for designing efficient distributed algorithms. While it has been extensively studied in the classic LOCAL model that uses unlimited bandwidth, much less is known in the…

Data Structures and Algorithms · Computer Science 2024-05-14 Magnús M. Halldórsson , Yannic Maus , Saku Peltonen

In the framework of the probabilistic method in combinatorics, we revisit the entropy compression method clarifying the setting in which it can be applied and providing a theorem yielding a general constructive criterion. We finally…

Combinatorics · Mathematics 2019-12-12 Rogério G. Alves , Aldo Procacci , Remy Sanchis

The Quantum Satisfiability problem generalizes the Boolean satisfiability problem to the quantum setting by replacing classical clauses with local projectors. The Quantum Lov\'asz Local Lemma gives a sufficient condition for a Quantum…

Quantum Physics · Physics 2017-02-14 Itai Arad , Or Sattath

Lecture notes for the Yale Computer Science course CPSC 4690/5690 Randomized Algorithms. Suitable for use as a supplementary text for an introductory graduate or advanced undergraduate course on randomized algorithms. Discusses tools from…

Data Structures and Algorithms · Computer Science 2025-12-22 James Aspnes

We point out a close connection between the Moser-Tardos algorithmic version of the Lov\'asz Local Lemma, a central tool in probabilistic combinatorics, and the cluster expansion of the hard core lattice gas in statistical mechanics. We…

Mathematical Physics · Physics 2013-06-18 Rogério Gomes Alves , Aldo Procacci

Many randomized algorithms can be derandomized efficiently using either the method of conditional expectations or probability spaces with low (almost-) independence. A series of papers, beginning with Luby (1993) and continuing with Berger…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

A nonconstructive proof can be used to prove the existence of an object with some properties without providing an explicit example of such an object. A special case is a probabilistic proof where we show that an object with required…

Discrete Mathematics · Computer Science 2013-10-29 Andrei Rumyantsev , Alexander Shen

We provide an alternative constructive proof of the Asymmetric Lov\'asz Local Lemma. Our proof uses the classic algorithmic framework of Moser and the analysis introduced by Giotis, Kirousis, Psaromiligkos, and Thilikos in "On the…

Discrete Mathematics · Computer Science 2015-05-12 Ioannis Giotis , Lefteris Kirousis , Kostas I. Psaromiligkos , Dimitrios M. Thilikos

Given an input $x$, and a search problem $F$, local computation algorithms (LCAs) implement access to specified locations of $y$ in a legal output $y \in F(x)$, using polylogarithmic time and space. Mansour et al., (2012), had previously…

Data Structures and Algorithms · Computer Science 2014-04-23 Omer Reingold , Shai Vardi

We consider column-sparse covering integer programs, a generalization of set cover, which have a long line of research of (randomized) approximation algorithms. We develop a new rounding scheme based on the Partial Resampling variant of the…

Data Structures and Algorithms · Computer Science 2023-10-13 Antares Chen , David G. Harris , Aravind Srinivasan

Learning-to-optimize leverages machine learning to accelerate optimization algorithms. While empirical results show tremendous improvements compared to classical optimization algorithms, theoretical guarantees are mostly lacking, such that…

Machine Learning · Computer Science 2025-06-02 Michael Sucker , Peter Ochs

We give a Markov chain based algorithm for sampling almost uniform solutions of constraint satisfaction problems (CSPs). Assuming a canonical setting for the Lov\'asz local lemma, where each constraint is violated by a small number of…

Data Structures and Algorithms · Computer Science 2021-04-13 Weiming Feng , Kun He , Yitong Yin

Large language models (LLMs) have proven to be highly effective for solving complex reasoning tasks. Surprisingly, their capabilities can often be improved by iterating on previously generated solutions. In this context, a reasoning plan…

Artificial Intelligence · Computer Science 2025-12-05 MohammadHossein Bateni , Vincent Cohen-Addad , Yuzhou Gu , Silvio Lattanzi , Simon Meierhans , Christopher Mohri

The trapping redundancy of a linear code is the number of rows of a smallest parity-check matrix such that no submatrix forms an $(a,b)$-trapping set. This concept was first introduced in the context of low-density parity-check (LDPC) codes…

Information Theory · Computer Science 2016-11-15 Yu Tsunoda , Yuichiro Fujiwara

In this paper, we apply the Clique Lov\'asz Local Lemma to provide sufficient conditions on memory and lifting degree for removing certain harmful combinatorial structures in spatially-coupled (SC) codes that negatively impact decoding…

Information Theory · Computer Science 2025-09-23 Lei Huang

The recently proven Quantum Lovasz Local Lemma generalises the well-known Lovasz Local Lemma. It states that, if a collection of subspace constraints are "weakly dependent", there necessarily exists a state satisfying all constraints. It…

Quantum Physics · Physics 2013-11-28 Toby S. Cubitt , Martin Schwarz

Partial penalized tests provide flexible approaches to testing linear hypotheses in high dimensional generalized linear models. However, because the estimators used in these tests are local minimizers of potentially non-convex…

Statistics Theory · Mathematics 2024-08-02 Tate Jacobson

We study the problem of sampling an approximately uniformly random satisfying assignment for atomic constraint satisfaction problems i.e. where each constraint is violated by only one assignment to its variables. Let $p$ denote the maximum…

Data Structures and Algorithms · Computer Science 2021-02-17 Vishesh Jain , Huy Tuan Pham , Thuy-Duong Vuong