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Given a graph and an integer $k$, Densest $k$-Subgraph is the algorithmic task of finding the subgraph on $k$ vertices with the maximum number of edges. This is a fundamental problem that has been subject to intense study for decades, with…

Computational Complexity · Computer Science 2023-03-31 Chris Jones , Aaron Potechin , Goutham Rajendran , Jeff Xu

The family of graphs that can be constructed from isolated vertices by disjoint union and graph join operations are called cographs. These graphs can be represented in a tree-like representation termed parse tree or cotree. In this paper,…

Data Structures and Algorithms · Computer Science 2018-08-29 Kona Harshita , N. Sadagopan

We consider two optimization problems related to finding dense subgraphs. The densest at-least-k-subgraph problem (DalkS) is to find an induced subgraph of highest average degree among all subgraphs with at least k vertices, and the densest…

Data Structures and Algorithms · Computer Science 2007-05-23 Reid Andersen

The graph partitioning problem is a well-known NP-hard problem. In this paper, we formulate a 0-1 quadratic integer programming model for the graph partitioning problem with vertex weight constraints and fixed vertex constraints, and…

Optimization and Control · Mathematics 2025-03-17 Wumwi Sun , Hongwei Liu , Xiaoyu Wang

We consider a natural generalization of Vertex Cover: the Subset Vertex Cover problem, which is to decide for a graph $G=(V,E)$, a subset $T\subseteq V$ and integer $k$, if $V$ has a subset $S$ of size at most $k$, such that $S$ contains at…

We show that every NP problem is polynomially equivalent to a simple combinatorial problem: the membership problem for a special class of digraphs. These classes are defined by means of shadows (projections) and by finitely many forbidden…

Computational Complexity · Computer Science 2007-06-27 Gabor Kun , Jaroslav Nesetril

Stochastic optimization algorithms with variance reduction have proven successful for minimizing large finite sums of functions. Unfortunately, these techniques are unable to deal with stochastic perturbations of input data, induced for…

Machine Learning · Statistics 2017-11-16 Alberto Bietti , Julien Mairal

This paper proposes a new general technique for maximal subgraph enumeration which we call proximity search, whose aim is to design efficient enumeration algorithms for problems that could not be solved by existing frameworks. To support…

Data Structures and Algorithms · Computer Science 2021-08-19 Alessio Conte , Andrea Marino , Roberto Grossi , Takeaki Uno , Luca Versari

Several popular language models represent local contexts in an input text $x$ as bags of words. Such representations are naturally encoded by a sequence graph whose vertices are the distinct words occurring in $x$, with edges representing…

Data Structures and Algorithms · Computer Science 2025-07-14 Sammy Khalife , Yann Ponty , Laurent Bulteau

For a class $\mathcal{G}$ of graphs, the objective of \textsc{Subgraph Complementation to} $\mathcal{G}$ is to find whether there exists a subset $S$ of vertices of the input graph $G$ such that modifying $G$ by complementing the subgraph…

Data Structures and Algorithms · Computer Science 2023-03-29 Dhanyamol Antony , Sagartanu Pal , R. B. Sandeep

We study the densest subgraph problem and its NP-hard densest at-most-$k$ subgraph variant through the lens of learning-augmented algorithms. We show that, given a reasonably accurate predictor that estimates whether a node belongs to the…

Data Structures and Algorithms · Computer Science 2026-04-16 Thai Bui , Luan Nguyen , Hoa T. Vu

We consider the problem of finding a subgraph of a given graph which maximizes a given function evaluated at its degree sequence. While the problem is intractable already for convex functions, we show that it can be solved in polynomial…

Combinatorics · Mathematics 2020-11-10 Shmuel Onn

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

The power dominating set (PDS) problem is the following extension of the well-known dominating set problem: find a smallest-size set of nodes $S$ that power dominates all the nodes, where a node $v$ is power dominated if (1) $v$ is in $S$…

Computational Complexity · Computer Science 2007-10-12 Ashkan Aazami , Michael D. Stilp

Let G be a simple connected graph with vertex set V(G) and edge set E(G. Each vertex of V(G) is colored by a color from the set of colors {c_1, c_2,\dots, c_{\alpha}}. We take a subset S of V(G), such that for every vertex v in V(G)\S, at…

Computational Geometry · Computer Science 2024-07-08 Bubai Manna

The distributed subgradient method (DSG) is a widely discussed algorithm to cope with large-scale distributed optimization problems in the arising machine learning applications. Most exisiting works on DSG focus on ideal communication…

Signal Processing · Electrical Eng. & Systems 2022-08-24 Zhaoyue Xia , Jun Du , Yong Ren

We study a natural generalization of the classical \textsc{Dominating Set} problem, called \textsc{Dominating Set with Quotas} (DSQ). In this problem, we are given a graph \( G \), an integer \( k \), and for each vertex \( v \in V(G) \), a…

Data Structures and Algorithms · Computer Science 2026-04-07 Sobyasachi Chatterjee , Sushmita Gupta , Saket Saurabh , Sanjay Seetharaman , Anannya Upasana

A vertex-subset graph problem $Q$ defines which subsets of the vertices of an input graph are feasible solutions. The reconfiguration version of a vertex-subset problem $Q$ asks whether it is possible to transform one feasible solution for…

Computational Complexity · Computer Science 2014-09-30 Amer E. Mouawad , Naomi Nishimura , Venkatesh Raman , Marcin Wrochna

A number of discrete and continuous optimization problems in machine learning are related to convex minimization problems under submodular constraints. In this paper, we deal with a submodular function with a directed graph structure, and…

Machine Learning · Computer Science 2013-09-27 Kiyohito Nagano , Yoshinobu Kawahara

In the constraint programming framework, state-of-the-art static and dynamic decomposition techniques are hard to apply to problems with complete initial constraint graphs. For such problems, we propose a hybrid approach of these techniques…

Computational Complexity · Computer Science 2008-12-18 Stephane Zampelli , Martin Mann , Yves Deville , Rolf Backofen
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