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In spite of the close connection between the evaluation of quantified Boolean formulas (QBF) and propositional satisfiability (SAT), tools and techniques which exploit structural properties of SAT instances are known to fail for QBF. This…

Data Structures and Algorithms · Computer Science 2017-11-08 Eduard Eiben , Robert Ganian , Sebastian Ordyniak

Tree ensembles have demonstrated state-of-the-art predictive performance across a wide range of problems involving tabular data. Nevertheless, the black-box nature of tree ensembles is a strong limitation, especially for applications with…

Machine Learning · Statistics 2025-10-30 Clément Bénard

In the first paper (part I) of this series of two, we introduce four novel definitions of the ODT problems: three for size-constrained trees and one for depth-constrained trees. These definitions are stated unambiguously through executable…

Machine Learning · Computer Science 2025-10-28 Xi He

The paper examines hierarchies for nondeterministic and deterministic ordered read-$k$-times Branching programs. The currently known hierarchies for deterministic $k$-OBDD models of Branching programs for $ k=o(n^{1/2}/\log^{3/2}n)$ are…

Computational Complexity · Computer Science 2024-04-05 Kamil Khadiev

The notion of directed treewidth was introduced by Johnson, Robertson, Seymour and Thomas [Journal of Combinatorial Theory, Series B, Vol 82, 2001] as a first step towards an algorithmic metatheory for digraphs. They showed that some…

Data Structures and Algorithms · Computer Science 2015-10-09 Mateus de Oliveira Oliveira

We consider bounded width CNF-formulas where the width is measured by popular graph width measures on graphs associated to CNF-formulas. Such restricted graph classes, in particular those of bounded treewidth, have been extensively studied…

Computational Complexity · Computer Science 2020-01-23 Stefan Mengel , Romain Wallon

We present a novel set of rigorous and computationally efficient topology-based complexity notions that exhibit a strong correlation with the generalization gap in modern deep neural networks (DNNs). DNNs show remarkable generalization…

Machine Learning · Computer Science 2024-12-17 Rayna Andreeva , Benjamin Dupuis , Rik Sarkar , Tolga Birdal , Umut Şimşekli

Binary Decision Diagrams (BDDs) are widely used for the representation of Boolean functions. Context-Free-Language Ordered Decision Diagrams (CFLOBDDs) are a plug-compatible replacement for BDDs -- roughly, they are BDDs augmented with a…

Symbolic Computation · Computer Science 2024-11-25 Xusheng Zhi , Thomas Reps

Decision Diagrams(DDs) are one of the most popular representations for boolean functions. They are widely used in the design and verification of circuits. Different types of DDs have been proven to represent important functions in…

Hardware Architecture · Computer Science 2022-09-27 Jan Kleinekathöfer , Alireza Mahzoon , Rolf Drechsler

We present a new approximation algorithm for the treewidth problem which finds an upper bound on the treewidth and constructs a corresponding tree decomposition as well. Our algorithm is a faster variation of Reed's classical algorithm. For…

Data Structures and Algorithms · Computer Science 2022-06-24 Mahdi Belbasi , Martin Fürer

We present a general method for converting any family of unsatisfiable CNF formulas that is hard for one of the simplest proof systems, tree resolution, into formulas that require large rank in any proof system that manipulates polynomials…

Computational Complexity · Computer Science 2009-12-04 Paul Beame , Trinh Huynh , Toniann Pitassi

Binary Decision Diagrams (BDDs) are a widely used data structure for efficient Boolean function representation. Context-Free-Language Ordered Binary Decision Diagrams (CFLOBDDs) are a recently introduced hierarchical data structure that…

Formal Languages and Automata Theory · Computer Science 2026-05-18 Meghana Aparna Sistla , Swarat Chaudhuri , Thomas W. Reps

Monadic second order logic (MSO2) plays an important role in parameterized complexity due to the Courcelle's theorem. This theorem states that the problem of checking if a given graph has a property specified by a given MSO2 formula can be…

Artificial Intelligence · Computer Science 2026-04-13 Petr Kučera , Petr Martinek

This paper presents a new compressed representation of Boolean functions, called CFLOBDDs (for Context-Free-Language Ordered Binary Decision Diagrams). They are essentially a plug-compatible alternative to BDDs (Binary Decision Diagrams),…

Symbolic Computation · Computer Science 2024-08-30 Meghana Sistla , Swarat Chaudhuri , Thomas Reps

A decision tree recursively splits a feature space $\mathbb{R}^{d}$ and then assigns class labels based on the resulting partition. Decision trees have been part of the basic machine-learning toolkit for decades. A large body of work treats…

To increase the interpretability and prediction accuracy of the Machine Learning (ML) models, visualization of ML models is a key part of the ML process. Decision Trees (DTs) are essential in machine learning (ML) because they are used to…

Machine Learning · Computer Science 2023-05-31 Boris Kovalerchuk Andrew Dunn , Alex Worland , Sridevi Wagle

A resolving set $S$ of a graph $G$ is a subset of its vertices such that no two vertices of $G$ have the same distance vector to $S$. The Metric Dimension problem asks for a resolving set of minimum size, and in its decision form, a…

Computational Complexity · Computer Science 2019-07-19 Édouard Bonnet , Nidhi Purohit

It is known that any planar graph with diameter D has treewidth O(D), and this fact has been used as the basis for several planar graph algorithms. We investigate the extent to which similar relations hold in other graph families. We show…

Combinatorics · Mathematics 2010-01-21 David Eppstein

Decision trees and random forest remain highly competitive for classification on medium-sized, standard datasets due to their robustness, minimal preprocessing requirements, and interpretability. However, a single tree suffers from high…

Machine Learning · Statistics 2025-12-02 Cencheng Shen , Yuexiao Dong , Carey E. Priebe

In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent graph models commonly used for these purposes are fault…

Other Computer Science · Computer Science 2023-10-10 L. A. Jimenez-Roa , T. Heskes , M. Stoelinga