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 concerns a different problem (such as traversal, finding paths, trees, and flows), decomposing large graphs is often an important subproblem for complexity reduction or parallelization. This report is a summary of discussions that happened at Dagstuhl seminar 23331 on "Recent Trends in Graph Decomposition" and presents currently open problems and future directions in the area of (hyper)graph decomposition
Human exploration of large data sets becomes increasingly difficult with growing amounts of data. Fo...
We are facing challenges at all levels ranging from infras-tructures to programming models for manag...
The decomposition of graphs refers to the process of breaking down a complex graph into simpler, sma...
Large networks are useful in a wide range of applications. Sometimes problem instances are composed ...
© 2019 IEEE. Graph decomposition has been widely used to analyze real-life networks from different p...
The structure of large networks models and Internet graphs in the autonomous system can be character...
Graphs are very important parts of Big Data and widely used for modelling complex structured data wi...
© 1989-2012 IEEE. Hypergraphs are generalizations of graphs where the (hyper)edges can connect any n...
This report documents the program and outcomes of Dagstuhl Seminar 18241 ``High-performance Graph Al...
International audienceNatural graphs, such as social networks, email graphs, or instant messaging pa...
Network decomposition is a central tool in distributed graph algorithms. We present two improvements...
WWW 2015: 24th International World Wide Web Conference, Florence, Italy, 18-22 May 2015Analyzing and...
Solving large systems of equations is a problem often encountered in engineering disciplines. Howeve...
The structure of large graphs can be revealed by partitioning graphs to smaller parts, which are eas...
This report documents the program and the outcomes of Dagstuhl Seminar 14461 “High- per-formance Gra...
Human exploration of large data sets becomes increasingly difficult with growing amounts of data. Fo...
We are facing challenges at all levels ranging from infras-tructures to programming models for manag...
The decomposition of graphs refers to the process of breaking down a complex graph into simpler, sma...
Large networks are useful in a wide range of applications. Sometimes problem instances are composed ...
© 2019 IEEE. Graph decomposition has been widely used to analyze real-life networks from different p...
The structure of large networks models and Internet graphs in the autonomous system can be character...
Graphs are very important parts of Big Data and widely used for modelling complex structured data wi...
© 1989-2012 IEEE. Hypergraphs are generalizations of graphs where the (hyper)edges can connect any n...
This report documents the program and outcomes of Dagstuhl Seminar 18241 ``High-performance Graph Al...
International audienceNatural graphs, such as social networks, email graphs, or instant messaging pa...
Network decomposition is a central tool in distributed graph algorithms. We present two improvements...
WWW 2015: 24th International World Wide Web Conference, Florence, Italy, 18-22 May 2015Analyzing and...
Solving large systems of equations is a problem often encountered in engineering disciplines. Howeve...
The structure of large graphs can be revealed by partitioning graphs to smaller parts, which are eas...
This report documents the program and the outcomes of Dagstuhl Seminar 14461 “High- per-formance Gra...
Human exploration of large data sets becomes increasingly difficult with growing amounts of data. Fo...
We are facing challenges at all levels ranging from infras-tructures to programming models for manag...
The decomposition of graphs refers to the process of breaking down a complex graph into simpler, sma...