5 citations · 5 across the 2 of their papers we have counts for
6 papers
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…
Jaccard-constrained dense subgraph discovery
Chamalee Wickrama Arachchi, Nikolaj Tatti
Finding dense subgraphs is a core problem in graph mining with many applications in diverse domains. At the same time many real-world networks vary over time, that is, the dataset…
Fast likelihood-based change point detection
Nikolaj Tatti
Change point detection plays a fundamental role in many real-world applications, where the goal is to analyze and monitor the behaviour of a data stream. In this paper, we study ch…
Ranking with submodular functions on the fly
Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
Maximizing submodular functions have been studied extensively for a wide range of subset-selection problems. However, much less attention has been given to the role of submodularit…
Maintaining AUC and -measure over time
Nikolaj Tatti
Measuring the performance of a classifier is a vital task in machine learning. The running time of an algorithm that computes the measure plays a very small role in an offline sett…
Interactive and Iterative Discovery of Entity Network Subgraphs
Hao Wu, Maoyuan Sun, Jilles Vreeken +3
Graph mining to extract interesting components has been studied in various guises, e.g., communities, dense subgraphs, cliques. However, most existing works are based on notions of…