6 papers
Finding coherent node groups in directed graphs
Iiro Kumpulainen, Nikolaj Tatti
Grouping the nodes of a graph into clusters is a standard technique for studying networks. We study a problem where we are given a directed network and are asked to partition the g…
The Densest SWAMP problem: subhypergraphs with arbitrary monotonic partial edge rewards
Vedangi Bengali, Nikolaj Tatti, Iiro Kumpulainen +2
We consider a generalization of the densest subhypergraph problem where nonnegative rewards are given for including partial hyperedges in a dense subhypergraph. Prior work addresse…
Improved Hardness and Approximations for Cardinality-Based Minimum - Cuts Problems in Hypergraphs
Florian Adriaens, Vedangi Bengali, Iiro Kumpulainen +2
In hypergraphs, an edge that crosses a cut (i.e., a bipartition of nodes) can be split in several ways, depending on how many nodes are placed on each side of the cut. A cardinalit…
Max-Min Diversification with Asymmetric Distances
Iiro Kumpulainen, Florian Adriaens, Nikolaj Tatti
One of the most well-known and simplest models for diversity maximization is the Max-Min Diversification (MMD) model, which has been extensively studied in the data mining and data…
Dense Subgraph Discovery Meets Strong Triadic Closure
Chamalee Wickrama Arachchi, Iiro Kumpulainen, Nikolaj Tatti
Finding dense subgraphs is a core problem with numerous graph mining applications such as community detection in social networks and anomaly detection. However, in many real-world…
From your Block to our Block: How to Find Shared Structure between Stochastic Block Models over Multiple Graphs
Iiro Kumpulainen, Sebastian Dalleiger, Jilles Vreeken +1
Stochastic Block Models (SBMs) are a popular approach to modeling single real-world graphs. The key idea of SBMs is to partition the vertices of the graph into blocks with similar…