Zobrazeno 1 - 10
of 229
pro vyhledávání: '"Marcelo, Fonseca"'
Addressing the challenges of processing massive graphs, which are prevalent in diverse fields such as social, biological, and technical networks, we introduce HeiStreamE and FreightE, two innovative (buffered) streaming algorithms designed for effici
Externí odkaz:
http://arxiv.org/abs/2402.11980
Increasing the connectivity of a graph is a pivotal challenge in robust network design. The weighted connectivity augmentation problem is a common version of the problem that takes link costs into consideration. The problem is then to find a minimum
Externí odkaz:
http://arxiv.org/abs/2402.07753
Autor:
Ajwani, Deepak, Bisseling, Rob H., Casel, Katrin, Çatalyürek, Ümit V., Chevalier, Cédric, Chudigiewitsch, Florian, Faraj, Marcelo Fonseca, Fellows, Michael, Gottesbüren, Lars, Heuer, Tobias, Karypis, George, Kaya, Kamer, Lacki, Jakub, Langguth, Johannes, Li, Xiaoye Sherry, Mayer, Ruben, Meintrup, Johannes, Mizutani, Yosuke, Pellegrini, François, Petrini, Fabrizio, Rosamond, Frances, Safro, Ilya, Schlag, Sebastian, Schulz, Christian, Sharma, Roohani, Strash, Darren, Sullivan, Blair D., Uçar, Bora, Yzelman, Albert-Jan
Large networks are useful in a wide range of applications. Sometimes problem instances are composed of billions of entities. Decomposing and analyzing these structures helps us gain new insights about our surroundings. Even if the final application c
Externí odkaz:
http://arxiv.org/abs/2310.11812
Autor:
Faraj, Marcelo Fonseca
(Hyper)Graph decomposition is a family of problems that aim to break down large (hyper)graphs into smaller sub(hyper)graphs for easier analysis. The importance of this lies in its ability to enable efficient computation on large and complex (hyper)gr
Externí odkaz:
http://arxiv.org/abs/2308.15617
Partitioning the vertices of a (hyper)graph into k roughly balanced blocks such that few (hyper)edges run between blocks is a key problem for large-scale distributed processing. A current trend for partitioning huge (hyper)graphs using low computatio
Externí odkaz:
http://arxiv.org/abs/2302.06259
Local clustering aims to identify a cluster within a given graph that includes a designated seed node or a significant portion of a group of seed nodes. This cluster should be well-characterized, i.e., it has a high number of internal edges and a low
Externí odkaz:
http://arxiv.org/abs/2301.07145
In this study, we address the complex issue of graph clustering in signed graphs, which are characterized by positive and negative weighted edges representing attraction and repulsion among nodes, respectively. The primary objective is to efficiently
Externí odkaz:
http://arxiv.org/abs/2208.13618
Autor:
Çatalyürek, Ümit V., Devine, Karen D., Faraj, Marcelo Fonseca, Gottesbüren, Lars, Heuer, Tobias, Meyerhenke, Henning, Sanders, Peter, Schlag, Sebastian, Schulz, Christian, Seemaier, Daniel, Wagner, Dorothea
In recent years, significant advances have been made in the design and evaluation of balanced (hyper)graph partitioning algorithms. We survey trends of the last decade in practical algorithms for balanced (hyper)graph partitioning together with futur
Externí odkaz:
http://arxiv.org/abs/2205.13202
A widely-used operation on graphs is local clustering, i.e., extracting a well-characterized community around a seed node without the need to process the whole graph. Recently local motif clustering has been proposed: it looks for a local cluster bas
Externí odkaz:
http://arxiv.org/abs/2205.06176