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We introduce a generalized framework for studying higher-order versions of the multiscale method known as Localized Orthogonal Decomposition. Through a suitable reformulation, we are able to accommodate both conforming and nonconforming…

Numerical Analysis · Mathematics 2025-06-25 Moritz Hauck , Alexei Lozinski , Roland Maier

We consider the problem of classifying trajectories on a discrete or discretised 2-dimensional manifold modelled by a simplicial complex. Previous works have proposed to project the trajectories into the harmonic eigenspace of the Hodge…

Social and Information Networks · Computer Science 2025-05-22 Vincent P. Grande , Josef Hoppe , Florian Frantzen , Michael T. Schaub

Topological phases of matter are often described using auxiliary systems in one extra dimension. I review the one-dimensional cluster state--the simplest quantum state with Symmetry-Protected Topological (SPT) order--as a toy model of…

High Energy Physics - Theory · Physics 2022-01-10 Bartlomiej Czech

This paper establishes the separation of complexity classes $\mathbf{P}$ and $\mathbf{NP}$ through a novel homological algebraic approach grounded in category theory. We construct the computational category $\mathbf{Comp}$, embedding…

Computational Complexity · Computer Science 2025-12-22 Jian-Gang Tang

Efficient computation of shortest cycles which form a homology basis under $\mathbb{Z}_2$-additions in a given simplicial complex $\mathcal{K}$ has been researched actively in recent years. When the complex $\mathcal{K}$ is a weighted graph…

Algebraic Topology · Mathematics 2018-01-30 Tamal K. Dey , Tianqi Li , Yusu Wang

We propose a nearest neighbor based clustering algorithm that results in a naturally defined hierarchy of clusters. In contrast to the agglomerative and divisive hierarchical clustering algorithms, our approach is not dependent on the…

Data Structures and Algorithms · Computer Science 2022-03-16 Kaan Gokcesu , Hakan Gokcesu

Multi-homogeneous polynomial systems arise in many applications. We provide bit complexity estimates for solving them which, up to a few extra other factors, are quadratic in the number of solutions and linear in the height of the input…

Symbolic Computation · Computer Science 2017-12-12 Mohab Safey El Din , Eric Schost

In this paper we study the hardness of the syndrome decoding problem over finite rings endowed with the Lee metric. We first prove that the decisional version of the problem is NP-complete, by a reduction from the $3$-dimensional matching…

Information Theory · Computer Science 2022-04-04 Violetta Weger , Karan Khathuria , Anna-Lena Horlemann , Massimo Battaglioni , Paolo Santini , Edoardo Persichetti

This paper describes an entropy regularization term for vector quantization (VQ) based on the analysis of persistent homology of the VQ embeddings. Higher embedding entropy positively correlates with higher codebook utilization, mitigating…

Machine Learning · Computer Science 2022-11-29 Ivan Volkov

Cycle representatives of persistent homology classes can be used to provide descriptions of topological features in data. However, the non-uniqueness of these representatives creates ambiguity and can lead to many different interpretations…

Algebraic Topology · Mathematics 2021-10-19 Lu Li , Connor Thompson , Gregory Henselman-Petrusek , Chad Giusti , Lori Ziegelmeier

Given an $n$-vertex non-negatively real-weighted graph $G$, whose vertices are partitioned into a set of $k$ clusters, a \emph{clustered network design problem} on $G$ consists of solving a given network design optimization problem on $G$,…

Data Structures and Algorithms · Computer Science 2018-02-01 Mattia D'Emidio , Luca Forlizzi , Daniele Frigioni , Stefano Leucci , Guido Proietti

The parameterized complexity of problems is often studied with respect to the size of their optimal solutions. However, for a maximization problem, the size of the optimal solution can be very large, rendering algorithms parameterized by it…

Data Structures and Algorithms · Computer Science 2015-03-24 Meirav Zehavi

The problem of nearest neighbor condensing has enjoyed a long history of study, both in its theoretical and practical aspects. In this paper, we introduce the problem of weighted distance nearest neighbor condensing, where one assigns…

Machine Learning · Computer Science 2023-10-25 Lee-Ad Gottlieb , Timor Sharabi , Roi Weiss

Similarity search (nearest neighbor search) is a problem of pursuing the data items whose distances to a query item are the smallest from a large database. Various methods have been developed to address this problem, and recently a lot of…

Data Structures and Algorithms · Computer Science 2014-08-14 Jingdong Wang , Heng Tao Shen , Jingkuan Song , Jianqiu Ji

A secure set $S$ in a graph is defined as a set of vertices such that for any $X\subseteq S$ the majority of vertices in the neighborhood of $X$ belongs to $S$. It is known that deciding whether a set $S$ is secure in a graph is…

Computational Complexity · Computer Science 2017-07-11 Bernhard Bliem , Stefan Woltran

With higher-order neighborhood information of graph network, the accuracy of graph representation learning classification can be significantly improved. However, the current higher order graph convolutional network has a large number of…

Machine Learning · Computer Science 2019-08-05 FangYuan Lei , Xun Liu , QingYun Dai , Bingo Wing-Kuen Ling , Huimin Zhao , Yan Liu

In the deletion version of the list homomorphism problem, we are given graphs G and H, a list L(v) that is a subset of V(H) for each vertex v of G, and an integer k. The task is to decide whether there exists a subset W of V(G) of size at…

Data Structures and Algorithms · Computer Science 2013-08-06 Rajesh Chitnis , Laszlo Egri , Daniel Marx

In graph modification problems, one is given a graph G and the goal is to apply a minimum number of modification operations (such as edge deletions) to G such that the resulting graph fulfills a certain property. For example, the Cluster…

Data Structures and Algorithms · Computer Science 2016-06-13 Christian Komusiewicz , André Nichterlein , Rolf Niedermeier

To better understand complexity in neural networks, we theoretically investigate the idealised phenomenon of lossless network compressibility, whereby an identical function can be implemented with fewer hidden units. In the setting of…

Machine Learning · Computer Science 2024-05-27 Matthew Farrugia-Roberts

In this paper we design {\sf FPT}-algorithms for two parameterized problems. The first is \textsc{List Digraph Homomorphism}: given two digraphs $G$ and $H$ and a list of allowed vertices of $H$ for every vertex of $G$, the question is…

Data Structures and Algorithms · Computer Science 2015-09-25 Eunjung Kim , Christophe Paul , Ignasi Sau , Dimitrios M. Thilikos