2 citations · 4 across the 11 of their papers we have counts for
11 papers
Simple Algorithms for Bad Triangle Transversals with Applications to Correlation Clustering
Florian Adriaens, Nikolaj tatti
The Bad Triangle Transversal (BTT) problem asks for the smallest set of edges that need to be removed from a given signed graph, so that the resulting graph does not have a bad tri…
Approximating splits for decision trees quickly in sparse data streams
Nikolaj Tatti
Decision trees are one of the most popular classifiers in the machine learning literature. While the most common decision tree learning algorithms treat data as a batch, numerous a…
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…
Fair Diversity Maximization with Few Representatives
Florian Adriaens, Nikolaj Tatti
Diversity maximization problem is a well-studied problem where the goal is to find diverse items. Fair diversity maximization aims to select a diverse subset of items from…
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…
Node ranking in labeled networks
Chamalee Wickrama Arachchi, Nikolaj Tatti
The entities in directed networks arising from real-world interactions are often naturally organized under some hierarchical structure. Given a directed, weighted, graph with edges…
Fair densest subgraph across multiple graphs
Chamalee Wickrama Arachchi, Nikolaj Tatti
Many real-world networks can be modeled as graphs. Finding dense subgraphs is a key problem in graph mining with applications in diverse domains. In this paper, we consider two var…
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…
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…
Multilayer Correlation Clustering
Atsushi Miyauchi, Florian Adriaens, Francesco Bonchi +1
We establish Multilayer Correlation Clustering, a novel generalization of Correlation Clustering to the multilayer setting. In this model, we are given a series of inputs of Correl…