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Recent successes of game-theoretic formulations in ML have caused a resurgence of research interest in differentiable games. Overwhelmingly, that research focuses on methods and upper bounds on their speed of convergence. In this work, we…

Machine Learning · Computer Science 2020-09-16 Adam Ibrahim , Waïss Azizian , Gauthier Gidel , Ioannis Mitliagkas

Low-degree polynomials have emerged as a powerful paradigm for providing evidence of statistical-computational gaps across a variety of high-dimensional statistical models [Wein25]. For detection problems -- where the goal is to test a…

Machine Learning · Statistics 2026-01-06 Alexandra Carpentier , Simone Maria Giancola , Christophe Giraud , Nicolas Verzelen

Multiple Tensor-Times-Matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-03 Hussam Al Daas , Grey Ballard , Laura Grigori , Suraj Kumar , Kathryn Rouse

We consider the class of conditional graph patterns (\emph{CGPs}) that allow user to query data graphs with complex patterns that contain negation and predicates. To overcome the prohibitive cost of subgraph isomorphism, we consider…

Databases · Computer Science 2022-07-27 Houari Mahfoud

Dense subgraph extraction is a fundamental problem in graph analysis and data mining, aimed at identifying cohesive and densely connected substructures within a given graph. It plays a crucial role in various domains, including social…

Data Structures and Algorithms · Computer Science 2024-03-01 Chia-Yang Hung , Chih-Ya Shen

We introduce a new class of extremum seeking controllers able to achieve fixed time convergence to the solution of optimization problems defined by static and dynamical systems. Unlike existing approaches in the literature, the convergence…

Optimization and Control · Mathematics 2019-12-17 Jorge I. Poveda , Miroslav Krstic

Two-level logic minimization is a central problem in logic synthesis, and has applications in reliability analysis and automated reasoning. This paper represents a method of minimizing Boolean sum of products function with binary decision…

Data Structures and Algorithms · Computer Science 2012-03-29 Debajit Sensarma , Subhashis Banerjee , Krishnendu Basuli , Saptarshi Naskar , Samar Sen Sarma

A stable cutset is a set of vertices $S$ of a connected graph, that is pairwise non-adjacent and when deleting $S$, the graph becomes disconnected. Determining the existence of a stable cutset in a graph is known to be NP-complete. In this…

Data Structures and Algorithms · Computer Science 2025-10-13 Mats Vroon , Hans L. Bodlaender

One of the main hypotheses in fine-grained complexity is that All-Pairs Shortest Paths (APSP) for $n$-node graphs requires $n^{3-o(1)}$ time. Another famous hypothesis is that the $3$SUM problem for $n$ integers requires $n^{2-o(1)}$ time.…

Computational Complexity · Computer Science 2020-07-29 Virginia Vassilevska Williams , Yinzhan Xu

We investigate the complexity of three optimization problems in Boolean propositional logic related to information theory: Given a conjunctive formula over a set of relations, find a satisfying assignment with minimal Hamming distance to a…

Computational Complexity · Computer Science 2022-10-13 Mike Behrisch , Miki Hermann , Stefan Mengel , Gernot Salzer

Algorithms which compute properties over graphs have always been of interest in computer science, with some of the fundamental algorithms, such as Dijkstra's algorithm, dating back to the 50s. Since the 70s there as been interest in…

Data Structures and Algorithms · Computer Science 2017-10-31 Daniel P. Martin

We show optimality, in a well-defined sense, using cumulative sum (CUSUM) charts for detecting changes in distributions. We consider a setting with multiple changes between two known distributions. This result advocates the use of…

Methodology · Statistics 2012-05-10 F. Din-Houn Lau , Axel Gandy

Many applications require solving sequences of related mixed-integer linear programs. We introduce a class of parametric disjunctive inequalities (PDIs), obtained by reusing the disjunctive proofs of optimality from prior solves to…

Optimization and Control · Mathematics 2025-11-21 Shannon Kelley , Aleksandr M. Kazachkov , Ted Ralphs

Linear diagrams are an effective way to visualize set-based data by representing elements as columns and sets as rows with one or more horizontal line segments, whose vertical overlaps with other rows indicate set intersections and their…

Computational Geometry · Computer Science 2022-08-18 Alexander Dobler , Martin Nöllenburg

The subset sum problem is one of the simplest and most fundamental NP-hard problems in combinatorial optimization. We consider two extensions of this problem: The subset sum problem with digraph constraint (SSG) and subset sum problem with…

Discrete Mathematics · Computer Science 2020-06-24 Frank Gurski , Dominique Komander , Carolin Rehs

The Restricted Shortest Path (RSP) problem, also known as the Delay-Constrained Least-Cost (DCLC) problem, is an NP-hard bicriteria optimization problem on graphs with $n$ vertices and $m$ edges. In a graph where each edge is assigned a…

Data Structures and Algorithms · Computer Science 2019-11-05 David Holzmüller

We consider the following string matching problem on a node-labeled graph $G=(V,E)$: given a pattern string $P$, decide whether there exists a path in $G$ whose concatenation of node labels equals $P$. This is a basic primitive in various…

Computational Complexity · Computer Science 2020-03-05 Massimo Equi , Veli Mäkinen , Alexandru I. Tomescu

We present the first truly subcubic, combinatorial algorithm for detecting an induced $4$-cycle in a graph. The running time is $O(n^{2.84})$ on $n$-node graphs, thus separating the task of detecting induced $4$-cycles from detecting…

Data Structures and Algorithms · Computer Science 2026-01-12 Amir Abboud , Shyan Akmal , Nick Fischer

Effective causal discovery is essential for learning the causal graph from observational data. The linear non-Gaussian acyclic model (LiNGAM) operates under the assumption of a linear data generating process with non-Gaussian noise in…

Machine Learning · Computer Science 2025-02-28 Hans Jarett J. Ong , Brian Godwin S. Lim , Renzo Roel P. Tan , Kazushi Ikeda

We observe that certain large-clique graph triangulations can be useful to reduce both computational and space requirements when making queries on mixed stochastic/deterministic graphical models. We demonstrate that many of these…

Artificial Intelligence · Computer Science 2012-07-02 Chris Bartels , Jeff A. Bilmes
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