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Lov\'asz Local Lemma (LLL) is a probabilistic tool that allows us to prove the existence of combinatorial objects in the cases when standard probabilistic argument does not work (there are many partly independent conditions). LLL can be…

Data Structures and Algorithms · Computer Science 2010-12-03 Andrey Rumyantsev

Language prediction is constrained by informational entropy intrinsic to language, such that there exists a limit to how accurate any language model can become and equivalently a lower bound to language compression. The most efficient…

Computation and Language · Computer Science 2025-11-14 Benjamin L. Badger , Matthew Neligeorge

The Lovasz Local Lemma [EL75] is a powerful tool to non-constructively prove the existence of combinatorial objects meeting a prescribed collection of criteria. In his breakthrough paper [Bec91], Beck demonstrated that a constructive…

Data Structures and Algorithms · Computer Science 2009-05-21 Robin A. Moser , Gábor Tardos

In this letter we propose the use of physics techniques for entropy determination on constrained parameter optimization problems. The main feature of such techniques, the construction of an unbiased walk on energy space, suggests their use…

Statistical Mechanics · Physics 2009-11-07 A. R. Lima , M. Argollo de Menezes

The Lov\'{a}sz Local Lemma (LLL) is a powerful tool in probabilistic combinatorics which can be used to establish the existence of objects that satisfy certain properties. The breakthrough paper of Moser and Tardos and follow-up works…

Data Structures and Algorithms · Computer Science 2025-09-09 David G. Harris , Fotis Iliopoulos , Vladimir Kolmogorov

The maximum entropy method has recently been successfully introduced to a variety of natural language applications. In each of these applications, however, the power of the maximum entropy method is achieved at the cost of a considerable…

cmp-lg · Computer Science 2008-02-03 John D. Lafferty , Bernhard Suhm

Following the groundbreaking algorithm of Moser and Tardos for the Lovasz Local Lemma (LLL), there has been a plethora of results analyzing local search algorithms for various constraint satisfaction problems. The algorithms considered fall…

Discrete Mathematics · Computer Science 2020-08-20 Dimitris Achlioptas , Fotis Iliopoulos , Alistair Sinclair

The Lov\'asz Local Lemma is a versatile result in probability theory, characterizing circumstances in which a collection of $n$ `bad events', each occurring with probability at most $p$ and dependent on a set of underlying random variables,…

Data Structures and Algorithms · Computer Science 2025-02-18 Peter Davies-Peck

The Lovasz Local Lemma due to Erdos and Lovasz is a powerful tool in proving the existence of rare events. We present an extension of this lemma, which works well when the event to be shown to exist is a conjunction of individual events,…

Data Structures and Algorithms · Computer Science 2007-05-23 Aravind Srinivasan

We present a method to derive an upper bound for the entropy density of coupled map lattices with local interactions from local observations. To do this, we use an embedding technique being a combination of time delay and spatial embedding.…

Chaotic Dynamics · Physics 2009-10-31 Eckehard Olbrich , Rainer Hegger , Holger Kantz

The Lopsided Lovasz Local Lemma (LLLL) is a cornerstone probabilistic tool for showing that it is possible to avoid a collection of "bad" events as long as their probabilities and interdependencies are sufficiently small. The strongest…

Probability · Mathematics 2023-10-13 David G. Harris

We describe a method to computationally estimate the probability density function of a univariate random variable by applying the maximum entropy principle with some local conditions given by Gaussian functions. The estimation errors and…

Statistics Theory · Mathematics 2012-06-21 Mihail-Ioan Pop

The Lovasz Local Lemma [EL75] is a powerful tool to prove the existence of combinatorial objects meeting a prescribed collection of criteria. The technique can directly be applied to the satisfiability problem, yielding that a k-CNF formula…

Data Structures and Algorithms · Computer Science 2008-10-29 Robin A. Moser

Learned image compression methods have attracted great research interest and exhibited superior rate-distortion performance to the best classical image compression standards of the present. The entropy model plays a key role in learned…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Jingbo Lu , Leheng Zhang , Xingyu Zhou , Mu Li , Wen Li , Shuhang Gu

We develop a method of obtaining a hierarchy of new higher-order entropies in the context of compressible models with local and non-local diffusion and isentropic pressure. The local viscosity is allowed to degenerate as the density…

Analysis of PDEs · Mathematics 2019-08-07 Peter Constantin , Theodore D. Drivas , Roman Shvydkoy

Compressing word embeddings is important for deploying NLP models in memory-constrained settings. However, understanding what makes compressed embeddings perform well on downstream tasks is challenging---existing measures of compression…

Machine Learning · Computer Science 2020-01-16 Avner May , Jian Zhang , Tri Dao , Christopher Ré

We consider the recent formulation of the Algorithmic Lov\'asz Local Lemma [10,2,3] for finding objects that avoid `bad features', or `flaws'. It extends the Moser-Tardos resampling algorithm [17] to more general discrete spaces. At each…

Data Structures and Algorithms · Computer Science 2018-09-05 Vladimir Kolmogorov

Kim defined a very general combinatorial abstraction of the diameter of polytopes called subset partition graphs to study how certain combinatorial properties of such graphs may be achieved in lower bound constructions. Using Lov\'asz'…

Combinatorics · Mathematics 2012-03-08 Nicolai Hähnle

Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher…

Information Theory · Computer Science 2014-02-11 N. Jesper Larsson

Entropy and free-energy estimation are key in thermodynamic characterization of simulated systems ranging from spin models through polymers, colloids, protein structure, and drug-design. Current techniques suffer from being model specific,…

Statistical Mechanics · Physics 2019-10-30 Ram Avinery , Micha Kornreich , Roy Beck