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Ordered matchings, defined as graphs with linearly ordered vertices, where each vertex is connected to exactly one edge, play a crucial role in the area of ordered graphs and their homomorphisms. Therefore, we consider related problems from…

Computational Complexity · Computer Science 2025-12-01 Michal Čertík , Andreas Emil Feldmann , Jaroslav Nešetřil , Paweł Rzążewski

Thanks to its solid theoretical foundation, the SHAP framework is arguably one the most widely utilized frameworks for local explainability of ML models. Despite its popularity, its exact computation is known to be very challenging, proven…

Machine Learning · Computer Science 2024-05-28 Reda Marzouk , Colin de La Higuera

Existing computationally efficient methods for penalized likelihood GAM fitting employ iterative smoothness selection on working linear models (or working mixed models). Such schemes fail to converge for a non-negligible proportion of…

Methodology · Statistics 2015-11-13 Simon N. Wood

We study the consensus-halving problem of dividing an object into two portions, such that each of $n$ agents has equal valuation for the two portions. The $\epsilon$-approximate consensus-halving problem allows each agent to have an…

Computer Science and Game Theory · Computer Science 2018-08-09 Aris Filos-Ratsikas , Soren Kristoffer Stiil Frederiksen , Paul W. Goldberg , Jie Zhang

The crossing number of a graph is the minimum number of edge crossings that a graph can have when drawn in the plane. Determining this number, known as the Crossing Number problem, is a celebrated problem in combinatorial optimization. It…

Computational Geometry · Computer Science 2026-03-30 Petr Hliněný , Liana Khazaliya

We study the graphs formed from instances of the stable matching problem by connecting pairs of elements with an edge when there exists a stable matching in which they are matched. Our results include the NP-completeness of recognizing…

Discrete Mathematics · Computer Science 2020-10-20 David Eppstein

It is well known that sparse approximation problem is \textsf{NP}-hard under general dictionaries. Several algorithms have been devised and analyzed in the past decade under various assumptions on the \emph{coherence} $\mu$ of the…

Computational Complexity · Computer Science 2017-02-10 Ali Çivril

Estimating matrices in the symmetric positive-definite (SPD) cone is of interest for many applications ranging from computer vision to graph learning. While there exist various convex optimization-based estimators, they remain limited in…

Machine Learning · Computer Science 2025-03-24 Can Pouliquen , Mathurin Massias , Titouan Vayer

In this paper we propose a new approach for developing a proof that P=NP. We propose to use a polynomial-time reduction of a NP-complete problem to Linear Programming. Earlier such attempts used polynomial-time transformation which is a…

Computational Complexity · Computer Science 2023-02-20 Malay Dutta , Anjana K. Mahanta

We study the stable matching problem in non-bipartite graphs with incomplete but strict preference lists, where the edges have weights and the goal is to compute a stable matching of minimum or maximum weight. This problem is known to be…

Computer Science and Game Theory · Computer Science 2017-03-28 Linda Farczadi , Natália Guričanová

We study the task of bandit learning, also known as best-arm identification, under the assumption that the true reward function f belongs to a known, but arbitrary, function class F. We seek a general theory of bandit learnability, akin to…

Machine Learning · Computer Science 2025-06-18 Nataly Brukhim , Aldo Pacchiano , Miroslav Dudik , Robert Schapire

Swish is a card game in which players are given cards having symbols (hoops and balls), and find a valid superposition of cards, called a "swish." Dailly, Lafourcade, and Marcadet (FUN 2024) studied a generalized version of Swish and showed…

Data Structures and Algorithms · Computer Science 2026-01-15 Takashi Horiyama , Takehiro Ito , Jun Kawahara , Shin-ichi Minato , Akira Suzuki , Ryuhei Uehara , Yutaro Yamaguchi

Sparse linear regression is the well-studied inference problem where one is given a design matrix $\mathbf{A} \in \mathbb{R}^{M\times N}$ and a response vector $\mathbf{b} \in \mathbb{R}^M$, and the goal is to find a solution $\mathbf{x}…

Machine Learning · Computer Science 2022-02-17 Aparna Gupte , Vinod Vaikuntanathan

The Graph Pricing problem is among the fundamental problems whose approximability is not well-understood. While there is a simple combinatorial 1/4-approximation algorithm, the best hardness result remains at 1/2 assuming the Unique Games…

Data Structures and Algorithms · Computer Science 2014-11-06 Euiwoong Lee

Given a pair of graphs $\textbf{A}$ and $\textbf{B}$, the problems of deciding whether there exists either a homomorphism or an isomorphism from $\textbf{A}$ to $\textbf{B}$ have received a lot of attention. While graph homomorphism is…

Data Structures and Algorithms · Computer Science 2021-07-08 Silvia Butti , Victor Dalmau

The Induced Graph Matching problem asks to find k disjoint induced subgraphs isomorphic to a given graph H in a given graph G such that there are no edges between vertices of different subgraphs. This problem generalizes the classical…

Discrete Mathematics · Computer Science 2014-02-11 Danny Hermelin , Matthias Mnich , Erik Jan van Leeuwen

The Scarf complex for lattices is well understood and utilized. In 2014, the author expanded the use of the term Scarf complex to encompass an infinite set in $\mathbb{Z}^n$ that was generated via an action of a lattice…

Combinatorics · Mathematics 2014-10-09 Trevor McGuire

Given a satisfiable instance of 1-in-3 SAT, it is NP-hard to find a satisfying assignment for it, but it may be possible to efficiently find a solution subject to a weaker (not necessarily Boolean) predicate than `1-in-3'. There is a…

Computational Complexity · Computer Science 2025-08-21 Andrei Krokhin , Danny Vagnozzi

Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even…

Machine Learning · Computer Science 2016-11-14 Abram L. Friesen , Pedro Domingos

Discrete probabilistic programs (DPPs) provide a highly expressive formalism for compactly defining arbitrary finite probabilistic models. This expressivity comes at a price: DPP inference is PSPACE-hard. In this work, we show that DPP…

Data Structures and Algorithms · Computer Science 2026-04-29 Benedikt Peterseim , Milan Lopuhaä-Zwakenberg
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