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We answer two open questions by (Gruber, Holzer, Kutrib, 2009) on the state-complexity of representing sub- or superword closures of context-free grammars (CFGs): (1) We prove a (tight) upper bound of $2^{\mathcal{O}(n)}$ on the size of…

Formal Languages and Automata Theory · Computer Science 2014-10-24 Georg Bachmeier , Michael Luttenberger , Maximilian Schlund

Generalizing the notion of automatic complexity of individual strings due to Shallit and Wang, we define the automatic complexity $A(E)$ of an equivalence relation $E$ on a finite set $S$ of strings. We prove that the problem of determining…

Formal Languages and Automata Theory · Computer Science 2020-02-03 Bjørn Kjos-Hanssen

We introduce a new canonical form of lattices called the systematic normal form (SNF). We show that for every lattice there is an efficiently computable "nearby" SNF lattice, such that for any lattice one can solve lattice problems on its…

Computational Complexity · Computer Science 2016-04-27 Lior Eldar , Peter W. Shor

We furnish solid evidence, both theoretical and empirical, towards the existence of a deterministic algorithm for random sparse $\#\Omega(\log n)$-SAT instances, which computes the exact counting of satisfying assignments in sub-exponential…

Computational Complexity · Computer Science 2020-11-10 Giorgio Camerani

The Local Lemma is a fundamental tool of probabilistic combinatorics and theoretical computer science, yet there are hardly any natural problems known where it provides an asymptotically tight answer. The main theme of our paper is to…

Combinatorics · Mathematics 2016-04-21 Heidi Gebauer , Tibor Szabo , Gabor Tardos

Our proposed framework attempts to break the trade-off between performance and explainability by introducing an explainable-by-design convolutional neural network (CNN) based on the lateral inhibition mechanism. The ExplaiNet model consists…

Machine Learning · Computer Science 2024-11-04 Pantelis I. Kaplanoglou , Konstantinos Diamantaras

Causal inconsistency arises when the underlying causal graphs captured by generative models like \textit{Normalizing Flows} (NFs) are inconsistent with those specified in causal models like \textit{Struct Causal Models} (SCMs). This…

Machine Learning · Computer Science 2024-12-18 Qingyang Zhou , Kangjie Lu , Meng Xu

Modern conflict-driven clause-learning (CDCL) Boolean SAT solvers provide efficient automatic analysis of real-world feature models (FM) of systems ranging from cars to operating systems. It is well-known that solver-based analysis of…

Software Engineering · Computer Science 2015-07-30 Jia Hui Liang , Vijay Ganesh , Venkatesh Raman , Krzysztof Czarnecki

Let $F=\{\mathbf{p}_0,\ldots,\mathbf{p}_n\}$ be a collection of points in $\mathbb{R}^d.$ The set $F$ naturally gives rise to a family of iterated function systems consisting of contractions of the form $$S_i(\mathbf{x})=\lambda \mathbf{x}…

Dynamical Systems · Mathematics 2018-10-17 Simon Baker , Derong Kong

A typical approach to the joint analysis of multiple high-dimensional data views is to decompose each view's data matrix into three parts: a low-rank common-source matrix generated by common latent factors of all data views, a low-rank…

Machine Learning · Statistics 2024-08-05 Hai Shu

We extend the convergence law for sparse random graphs proven by Lynch to arbitrary relational languages. We consider a finite relational vocabulary $\sigma$ and a first order theory $T$ for $\sigma$ composed of symmetry and…

Combinatorics · Mathematics 2020-06-15 Lázaro Alberto Larrauri

We present a study of minimal unsatisfiable subsets (MUSs) of 2-CNF Boolean formulas, building on the Abbasizanjani-Kullmann classification of minimally unsatisfiable 2-CNFs (2-MUs). We start by giving a linear-time procedure for…

Data Structures and Algorithms · Computer Science 2026-03-12 Oliver Kullmann , Edward Clewer

The problem of when a given digraph contains a subdivision of a fixed digraph $F$ is considered. Bang-Jensen et al. laid out foundations for approaching this problem from the algorithmic point of view. In this paper we give further support…

Combinatorics · Mathematics 2017-08-08 Frédéric Havet , A. Karolinna Maia , Bojan Mohar

In this paper, we discussed CNF-SAT problem (NP-Complete problem) and analysis two solutions that can solve the problem, the PL-Resolution algorithm and the WalkSAT algorithm. PL-Resolution is a sound and complete algorithm that can be used…

Artificial Intelligence · Computer Science 2013-07-25 Xili Wang

We present a simple randomized algorithm that approximates the number of satisfying assignments of Boolean formulas in conjunctive normal form. To the best of our knowledge this is the first algorithm which approximates #k-SAT for any k >=…

Data Structures and Algorithms · Computer Science 2011-07-12 Marc Thurley

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

This paper investigates linear programming based branch-and-bound using general disjunctions, also known as stabbing planes, for solving integer programs. We derive the first sub-exponential lower bound (in the encoding length $L$ of the…

Optimization and Control · Mathematics 2023-09-13 Max Gläser , Marc E. Pfetsch

We present a definition of the class NP in combinatorial context as the set of languages of structures defined by finitely many forbidden lifted substructures. We apply this to special syntactically defined subclasses and show how they…

Combinatorics · Mathematics 2007-06-13 Gabor Kun , Jaroslav Nesetril

This article describes the solvability of HornSAT and CNFSAT. Unsatisfiable HornCNF have partially ordered set that is made by causation of each clauses. In this partially ordered set, Truth value assignment that is false in each clauses…

Computational Complexity · Computer Science 2013-01-01 Koji Kobayashi

Modern neural network architectures for large-scale learning tasks have substantially higher model complexities, which makes understanding, visualizing and training these architectures difficult. Recent contributions to deep learning…

Machine Learning · Computer Science 2024-10-30 Jayadeva , Himanshu Pant , Mayank Sharma , Abhimanyu Dubey , Sumit Soman , Suraj Tripathi , Sai Guruju , Nihal Goalla