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This paper initiates the study of I/O algorithms (minimizing cache misses) from the perspective of fine-grained complexity (conditional polynomial lower bounds). Specifically, we aim to answer why sparse graph problems are so hard, and why…

Data Structures and Algorithms · Computer Science 2017-12-06 Erik D. Demaine , Andrea Lincoln , Quanquan C. Liu , Jayson Lynch , Virginia Vassilevska Williams

For a given graph $G$, a depth-first search (DFS) tree $T$ of $G$ is an $r$-rooted spanning tree such that every edge of $G$ is either an edge of $T$ or is between a \textit{descendant} and an \textit{ancestor} in $T$. A graph $G$ together…

Data Structures and Algorithms · Computer Science 2023-07-21 Emmanuel Sam , Benjamin Bergougnoux , Petr A. Golovach , Nello Blaser

We generalize the fractional packing framework of Garg and Koenemann to the case of linear fractional packing problems over polyhedral cones. More precisely, we provide approximation algorithms for problems of the form $\max\{c^T x : Ax…

Data Structures and Algorithms · Computer Science 2016-12-19 Michael Holzhauser , Sven O. Krumke

A kernel of a directed graph is a subset of vertices that is both independent and absorbing (every vertex not in the kernel has an out-neighbour in the kernel). Not all directed graphs contain kernels, and computing a kernel or deciding…

Discrete Mathematics · Computer Science 2024-05-20 Bruno Jartoux

In this paper, we propose the novel problem of Subteam Replacement: given a team of people embedded in a social network to complete a certain task, and a subset of members - subteam - in this team which have become unavailable, find another…

Social and Information Networks · Computer Science 2021-11-12 Zhaoheng Li , Xinyu Pi , Mingyuan Wu , Hanghang Tong

In presence of sparse noise we propose kernel regression for predicting output vectors which are smooth over a given graph. Sparse noise models the training outputs being corrupted either with missing samples or large perturbations. The…

Machine Learning · Statistics 2018-11-07 Arun Venkitaraman , Pascal Frossard , Saikat Chatterjee

This paper introduces a novel graph signal processing framework for building graph-based models from classes of filtered signals. In our framework, graph-based modeling is formulated as a graph system identification problem, where the goal…

Machine Learning · Computer Science 2018-03-08 Hilmi E. Egilmez , Eduardo Pavez , Antonio Ortega

A commonly used paradigm for representing graphs is to use a vector that contains normalized frequencies of occurrence of certain motifs or sub-graphs. This vector representation can be used in a variety of applications, such as, for…

Machine Learning · Computer Science 2014-03-05 Pinar Yanardag , S. V. N. Vishwanathan

Algorithms for listing the subgraphs satisfying a given property (e.g.,being a clique, a cut, a cycle, etc.) fall within the general framework of set systems. A set system (U, F) uses a ground set U (e.g., the network nodes) and an…

Discrete Mathematics · Computer Science 2018-03-13 Alessio Conte , Roberto Grossi , Andrea Marino , Luca Versari

An independent vertex subset $S$ of the directed graph $G$ is a kernel if the set of out-neighbors of $S$ is $V(G)\setminus S$. An independent vertex subset $Q$ of $G$ is a quasi-kernel if the union of the first and second out-neighbors…

Combinatorics · Mathematics 2024-05-30 Péter L. Erdős , Ervin Győri , Tamás Róbert Mezei , Nika Salia , Mykhaylo Tyomkyn

Graphs are a powerful way to model interactions and relationships in data from a wide variety of application domains. In this setting, entities represented by vertices at the "center" of the graph are often more important than those…

Social and Information Networks · Computer Science 2014-11-06 Michael P. O'Brien , Blair D. Sullivan

Problems in scientific computing, such as distributing large sparse matrix operations, have analogous formulations as hypergraph partitioning problems. A hypergraph is a generalization of a traditional graph wherein "hyperedges" may connect…

Data Structures and Algorithms · Computer Science 2022-06-16 Justin Sybrandt , Ruslan Shaydulin , Ilya Safro

We show that Odd Cycle Transversal and Vertex Multiway Cut admit deterministic polynomial kernels when restricted to planar graphs and parameterized by the solution size. This answers a question of Saurabh. On the way to these results, we…

Data Structures and Algorithms · Computer Science 2018-12-13 Bart M. P. Jansen , Marcin Pilipczuk , Erik Jan van Leeuwen

We introduce propagation kernels, a general graph-kernel framework for efficiently measuring the similarity of structured data. Propagation kernels are based on monitoring how information spreads through a set of given graphs. They leverage…

Machine Learning · Statistics 2014-10-14 Marion Neumann , Roman Garnett , Christian Bauckhage , Kristian Kersting

We propose a simple, powerful, and flexible machine learning framework for (i) reducing the search space of computationally difficult enumeration variants of subset problems and (ii) augmenting existing state-of-the-art solvers with…

Machine Learning · Computer Science 2019-02-25 Juho Lauri , Sourav Dutta

This paper introduces a new kernel-based classifier by viewing kernel matrices as generalized graphs and leveraging recent progress in graph embedding techniques. The proposed method facilitates fast and scalable kernel matrix embedding,…

Machine Learning · Computer Science 2024-11-12 Cencheng Shen

While kernel methods and Graph Neural Networks offer complementary strengths, integrating the two has posed challenges in efficiency and scalability. The Graph Neural Tangent Kernel provides a theoretical bridge by interpreting GNNs through…

Machine Learning · Computer Science 2025-07-17 Lin Wang , Shijie Wang , Sirui Huang , Qing Li

In the NP-hard Edge Dominating Set problem (EDS) we are given a graph $G=(V,E)$ and an integer $k$, and need to determine whether there is a set $F\subseteq E$ of at most $k$ edges that are incident with all (other) edges of $G$. It is…

Data Structures and Algorithms · Computer Science 2019-01-14 Eva-Maria C. Hols , Stefan Kratsch

A graph is c-closed if every pair of vertices with at least c common neighbors is adjacent. The c-closure of a graph G is the smallest number such that G is c-closed. Fox et al. [ICALP '18] defined c-closure and investigated it in the…

Discrete Mathematics · Computer Science 2022-06-22 Tomohiro Koana , Christian Komusiewicz , Frank Sommer

We study the following two fixed-cardinality optimization problems (a maximization and a minimization variant). For a fixed $\alpha$ between zero and one we are given a graph and two numbers $k \in \mathbb{N}$ and $t \in \mathbb{Q}$. The…

Data Structures and Algorithms · Computer Science 2022-10-20 Tomohiro Koana , Christian Komusiewicz , André Nichterlein , Frank Sommer