Add to ORKGWe provide a rearrangement based algorithm for fast detection of subgraphs of $k$ vertices with long escape times for directed or undirected networks. Complementing other notions of densest subgraphs and graph cuts, our method is based on the mean hitting time required for a random walker to leave a designated set and hit the complement. We provide a new relaxation of this notion of hitting time on a given subgraph and use that relaxation to construct a fast subgraph detection algorithm and a generalization to $K$-partitioning schemes. Using a modification of the subgraph detector on each component, we propose a graph partitioner that identifies regions where random walks live for comparably large times. Importantly, our method implicitly r...
Dense subgraphs of sparse graphs (communities), which appear in most real-world complex networks, pl...
In this paper, we provide faster algorithms for computing variousfundamental quantities associated w...
Listing dense subgraphs is a fundamental task with a variety of network analytics applications. A lo...
While in many graph mining applications it is crucial to handle a stream of updates efficiently in t...
The problem of detecting dense subgraphs (communities) in large sparse graphs is inherent to many re...
In this paper we give sublinear-time distributed algorithms in the CONGEST model for subgraph detect...
How can we find patterns from an enormous graph with billions of vertices and edges? The subgraph en...
Extracting dense subgraphs from large graphs is a key prim-itive in a variety of graph mining applic...
The problem of graph clustering is a central optimization problem with various applications in numer...
We consider a variant of the clustering problem for a complete weighted graph. The aim is to partiti...
Multiple methods of finding the vertices belonging to a planted dense subgraph in a random dense $G(...
Finding community structures in social networks is considered to be a challenging task as many of th...
Large graphs are often used to simulate and model complex systems in variousresearch and application...
With the help of information technologies, we have access to very large networks, even with billions...
In this paper, we study the problem of discovering a timeline of events in a temporal network. We mo...
Dense subgraphs of sparse graphs (communities), which appear in most real-world complex networks, pl...
In this paper, we provide faster algorithms for computing variousfundamental quantities associated w...
Listing dense subgraphs is a fundamental task with a variety of network analytics applications. A lo...
While in many graph mining applications it is crucial to handle a stream of updates efficiently in t...
The problem of detecting dense subgraphs (communities) in large sparse graphs is inherent to many re...
In this paper we give sublinear-time distributed algorithms in the CONGEST model for subgraph detect...
How can we find patterns from an enormous graph with billions of vertices and edges? The subgraph en...
Extracting dense subgraphs from large graphs is a key prim-itive in a variety of graph mining applic...
The problem of graph clustering is a central optimization problem with various applications in numer...
We consider a variant of the clustering problem for a complete weighted graph. The aim is to partiti...
Multiple methods of finding the vertices belonging to a planted dense subgraph in a random dense $G(...
Finding community structures in social networks is considered to be a challenging task as many of th...
Large graphs are often used to simulate and model complex systems in variousresearch and application...
With the help of information technologies, we have access to very large networks, even with billions...
In this paper, we study the problem of discovering a timeline of events in a temporal network. We mo...
Dense subgraphs of sparse graphs (communities), which appear in most real-world complex networks, pl...
In this paper, we provide faster algorithms for computing variousfundamental quantities associated w...
Listing dense subgraphs is a fundamental task with a variety of network analytics applications. A lo...