Exact Algorithms for Exact Satisfiability and Number of Perfect Matchings

2006 ◽  
pp. 548-559 ◽  
Author(s):  
Andreas Björklund ◽  
Thore Husfeldt
Keyword(s):  
Exact Algorithms ◽  
Perfect Matchings

Exact Algorithms for Exact Satisfiability and Number of Perfect Matchings

Algorithmica ◽  
2007 ◽  
Vol 52 (2) ◽  
pp. 226-249 ◽  
Author(s):  
Andreas Björklund ◽  
Thore Husfeldt
Keyword(s):  
Exact Algorithms ◽  
Perfect Matchings

Efficient Computation of Representative Families with Applications in Parameterized and Exact Algorithms

2016 ◽  
Vol 63 (4) ◽  
pp. 1-60 ◽  
Author(s):  
Fedor V. Fomin ◽  
Daniel Lokshtanov ◽  
Fahad Panolan ◽  
Saket Saurabh
Keyword(s):  
Exact Algorithms ◽  
Efficient Computation

Efficient Directed Densest Subgraph Discovery

2021 ◽  
Vol 50 (1) ◽  
pp. 33-40
Author(s):  
Chenhao Ma ◽  
Yixiang Fang ◽  
Reynold Cheng ◽  
Laks V.S. Lakshmanan ◽  
Wenjie Zhang ◽  
...  
Keyword(s):  
Approximation Algorithms ◽  
State Of The Art ◽  
Exact Algorithms ◽  
Large Datasets ◽  
Dense Subgraph ◽  
Extensive Evaluation ◽  
Wide Range ◽  
Edge Graph ◽  
Community Mining ◽  
Densest Subgraph

Given a directed graph G, the directed densest subgraph (DDS) problem refers to the finding of a subgraph from G, whose density is the highest among all the subgraphs of G. The DDS problem is fundamental to a wide range of applications, such as fraud detection, community mining, and graph compression. However, existing DDS solutions suffer from efficiency and scalability problems: on a threethousand- edge graph, it takes three days for one of the best exact algorithms to complete. In this paper, we develop an efficient and scalable DDS solution. We introduce the notion of [x, y]-core, which is a dense subgraph for G, and show that the densest subgraph can be accurately located through the [x, y]-core with theoretical guarantees. Based on the [x, y]-core, we develop both exact and approximation algorithms. We have performed an extensive evaluation of our approaches on eight real large datasets. The results show that our proposed solutions are up to six orders of magnitude faster than the state-of-the-art.

scholarly journals Secure the IoT Networks as Epidemic Containment Game

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 156
Author(s):  
Juntao Zhu ◽  
Hong Ding ◽  
Yuchen Tao ◽  
Zhen Wang ◽  
Lanping Yu
Keyword(s):  
Heuristic Algorithms ◽  
Heuristic Method ◽  
Exact Algorithms ◽  
Epidemic Threshold ◽  
Solution Quality ◽  
Sis Model ◽  
Linear Programming Formulation ◽  
Iot Devices ◽  
General Graphs ◽  
The Internet Of Things

The spread of a computer virus among the Internet of Things (IoT) devices can be modeled as an Epidemic Containment (EC) game, where each owner decides the strategy, e.g., installing anti-virus software, to maximize his utility against the susceptible-infected-susceptible (SIS) model of the epidemics on graphs. The EC game’s canonical solution concepts are the Minimum/Maximum Nash Equilibria (MinNE/MaxNE). However, computing the exact MinNE/MaxNE is NP-hard, and only several heuristic algorithms are proposed to approximate the MinNE/MaxNE. To calculate the exact MinNE/MaxNE, we provide a thorough analysis of some special graphs and propose scalable and exact algorithms for general graphs. Especially, our contributions are four-fold. First, we analytically give the MinNE/MaxNE for EC on special graphs based on spectral radius. Second, we provide an integer linear programming formulation (ILP) to determine MinNE/MaxNE for the general graphs with the small epidemic threshold. Third, we propose a branch-and-bound (BnB) framework to compute the exact MinNE/MaxNE in the general graphs with several heuristic methods to branch the variables. Fourth, we adopt NetShiled (NetS) method to approximate the MinNE to improve the scalability. Extensive experiments demonstrate that our BnB algorithm can outperform the naive enumeration method in scalability, and the NetS can improve the scalability significantly and outperform the previous heuristic method in solution quality.

scholarly journals On Directed Versions of the Hajnal–Szemerédi Theorem

2015 ◽  
Vol 24 (6) ◽  
pp. 873-928 ◽  
Author(s):  
ANDREW TREGLOWN
Keyword(s):  
Directed Graph ◽  
Minimum Degree ◽  
Directed Graphs ◽  
Perfect Matchings ◽  
Large Order ◽  
Vertex Disjoint ◽  
Removal Lemma

We say that a (di)graph G has a perfect H-packing if there exists a set of vertex-disjoint copies of H which cover all the vertices in G. The seminal Hajnal–Szemerédi theorem characterizes the minimum degree that ensures a graph G contains a perfect Kr-packing. In this paper we prove the following analogue for directed graphs: Suppose that T is a tournament on r vertices and G is a digraph of sufficiently large order n where r divides n. If G has minimum in- and outdegree at least (1−1/r)n then G contains a perfect T-packing.In the case when T is a cyclic triangle, this result verifies a recent conjecture of Czygrinow, Kierstead and Molla [4] (for large digraphs). Furthermore, in the case when T is transitive we conjecture that it suffices for every vertex in G to have sufficiently large indegree or outdegree. We prove this conjecture for transitive triangles and asymptotically for all r ⩾ 3. Our approach makes use of a result of Keevash and Mycroft [10] concerning almost perfect matchings in hypergraphs as well as the Directed Graph Removal Lemma [1, 6].

scholarly journals Exact Algorithms for $L^1$-TV Regularization of Real-Valued or Circle-Valued Signals

2016 ◽  
Vol 38 (1) ◽  
pp. A614-A630 ◽  
Author(s):  
Martin Storath ◽  
Andreas Weinmann ◽  
Michael Unser
Keyword(s):  
Exact Algorithms ◽  
Tv Regularization
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