Explanipedia

Brain Ventricle Morphology Markers in Predicting Shunt Surgery Outcome in Idiopathic Normal-Pressure Hydrocephalus Open

Andrius Penkauskas, Eemeli Kuukkanen, Anssi Lipponen, Juhana Hakumäki, Juha Koikkalainen , et al. · 2025

Background Idiopathic normal pressure hydrocephalus (iNPH) is characterized by a clinical triad of symptoms: abnormal gait, memory problems, and urinary incontinence. Neuroimaging plays a crucial role in diagnosing iNPH. However, current r…

Finding Rule-Interpretable Non-Negative Data Representation Open

Matej Mihelciˇc, Pauli Miettinen · 2025

Fast Redescription Mining Using Locality-Sensitive Hashing Open

Maiju Karjalainen, Esther Galbrun, Pauli Miettinen · 2024

Redescription mining is a data analysis technique that has found applications in diverse fields. The most used redescription mining approaches involve two phases: finding matching pairs among data attributes and extending the pairs. This p…

Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations Open

Thibault Marette, Pauli Miettinen, Stefan Neumann · 2023

Finding (bi-)clusters in bipartite graphs is a popular data analysis approach. Analysts typically want to visualize the clusters, which is simple as long as the clusters are disjoint. However, many modern algorithms find overlapping cluste…

Differentially private tree-based redescription mining Open

Matej Mihelčić, Pauli Miettinen · 2023

Differential privacy provides a strong form of privacy and allows preserving most of the original characteristics of the dataset. Utilizing these benefits requires one to design specific differentially private data analysis algorithms. In …

Differentially Private Tree-Based Redescription Mining Open

Matej Mihelčić, Pauli Miettinen · 2022

Differential privacy provides a strong form of privacy and allows preserving most of the original characteristics of the dataset. Utilizing these benefits requires one to design specific differentially private data analysis algorithms. In …

Finding Rule-Interpretable Non-Negative Data Representation Open

Matej Mihelčić, Pauli Miettinen · 2022

Non-negative Matrix Factorization (NMF) is an intensively used technique for obtaining parts-based, lower dimensional and non-negative representation. Researchers in biology, medicine, pharmacy and other fields often prefer NMF over other …

[Title page iii] Open

James E. Bailey, Pauli Miettinen, Yun Sing Koh, Dacheng Tao, Xindong Wu · 2021

Biclustering and Boolean Matrix Factorization in Data Streams Open

Stefan Neumann, Pauli Miettinen · 2020

We study the clustering of bipartite graphs and Boolean matrix factorization in data streams. We consider a streaming setting in which the vertices from the left side of the graph arrive one by one together with all of their incident edges…

Recent Developments in Boolean Matrix Factorization Open

Pauli Miettinen, Stefan Neumann · 2020

The goal of Boolean Matrix Factorization (BMF) is to approximate a given binary matrix as the product of two low-rank binary factor matrices, where the product of the factor matrices is computed under the Boolean algebra. While the problem…

Recent Developments in Boolean Matrix Factorization Open

Pauli Miettinen, Stefan Neumann · 2020

The goal of Boolean Matrix Factorization (BMF) is to approximate a given binary matrix as the product of two low-rank binary factor matrices, where the product of the factor matrices is computed under the Boolean algebra. While the problem…

Frequent subgraph mining for biologically meaningful structural motifs Open

Sebastian Keller, Pauli Miettinen, Olga V. Kalinina · 2020

Identification of biologically relevant motifs in proteins is a long-standing problem in bioinformatics, especially when considering distantly related proteins where sequence analysis alone becomes increasingly difficult. Here we present a…

Lainvalmistelu tiedonhallinnan haasteena – tekoäly ratkaisuna? Open

Harriet Lonka, Anssi Keinänen, Eeva Ovaska, Kimmo Kiiski, Väinö Jääskinen , et al. · 2020

Tässä artikkelissa tarkastellaan käytännön lainvalmisteluprosessin mallintamisen pohjalta tekoälytyövälineiden hyödyntämisen mahdollisuuksia lainvalmistelun laadun parantamisessa. Tutkimuksessa on käytetty tapausesimerkkinä liikenne- ja vi…

HyGen: generating random graphs with hyperbolic communities Open

Saskia Metzler, Pauli Miettinen · 2019

Hybrid ASP-based Approach to Pattern Mining Open

Sergey Paramonov, Daria Stepanova, Pauli Miettinen · 2019

Detecting small sets of relevant patterns from a given data set is a central challenge in data mining. The relevance of a pattern is based on user-provided criteria; typically, all patterns that satisfy certain criteria are considered rele…

Algorithms for approximate subtropical matrix factorization Open

Sanjar Karaev, Pauli Miettinen · 2018

Matrix factorization methods are important tools in data mining and analysis. They can be used for many tasks, ranging from dimensionality reduction to visualization. In this paper we concentrate on the use of matrix factorizations for fin…

Latitude: A Model for Mixed Linear-Tropical Matrix Factorization Open

Sanjar Karaev, James Hook, Pauli Miettinen · 2018

Nonnegative matrix factorization (NMF) is one of the most frequently-used matrix factorization models in data analysis. A significant reason to the popularity of NMF is its interpretability and the `parts of whole' interpretation of its co…

Mining Redescriptions with Siren Open

Esther Galbrun, Pauli Miettinen · 2018

In many areas of science, scientists need to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions. For example, in biology, an important task is to …

From sets of good redescriptions to good sets of redescriptions Open

Janis Kalofolias, Esther Galbrun, Pauli Miettinen · 2018

Logistic-Tropical Decompositions and Nested Subgraphs Open

Sanjar Karaev, Saskia Metzler, Pauli Miettinen · 2018

Reductions for Frequency-Based Data Mining Problems Open

Stefan Neumann, Pauli Miettinen · 2017

Studying the computational complexity of problems is one of the - if not the - fundamental questions in computer science. Yet, surprisingly little is known about the computational complexity of many central problems in data mining. In this…

Algorithms for Approximate Subtropical Matrix Factorization Open

Sanjar Karaev, Pauli Miettinen · 2017

Matrix factorization methods are important tools in data mining and analysis. They can be used for many tasks, ranging from dimensionality reduction to visualization. In this paper we concentrate on the use of matrix factorizations for fin…

Redescription Mining: An Overview Open

Esther Galbrun, Pauli Miettinen · 2017

International audience

Hyperbolae are No Hyperbole: Modelling Communities That are Not Cliques Open

Saskia Metzler, Stephan Günnemann, Pauli Miettinen · 2016

Cliques are frequently used to model communities: a community is a set of nodes where each pair is equally likely to be connected. But studying real-world communities reveals that they have more structure than that. In particular, the node…

Analysing Political Opinions Using Redescription Mining Open

Esther Galbrun, Pauli Miettinen · 2016

International audience

What You Will Gain By Rounding: Theory and Algorithms for Rounding Rank Open

Stefan Neumann, Rainer Gemulla, Pauli Miettinen · 2016

When factorizing binary matrices, we often have to make a choice between using expensive combinatorial methods that retain the discrete nature of the data and using continuous methods that can be more efficient but destroy the discrete str…

Capricorn: An Algorithm for Subtropical Matrix Factorization Open

Sanjar Karaev, Pauli Miettinen · 2016

Max-times algebra, sometimes known as subtropical algebra, is a semi-ring over the nonnegative real numbers where the addition operation is the max function and the multiplication is the standard one.Factorizing a nonnegative matrix over t…

Interactive Constrained Boolean Matrix Factorization Open

Nelson Mukuze, Pauli Miettinen · 2016

Getting to Know the Unknown Unknowns: Destructive-Noise Resistant Boolean Matrix Factorization Open

Sanjar Karaev, Pauli Miettinen, Jilles Vreeken · 2015

Finding patterns in binary data is a classical problem in data mining, dating back to at least frequent itemset mining. More recently, approaches such as tiling and Boolean matrix factorization (BMF), have been proposed to find sets of pat…

Clustering Boolean tensors Open

Saskia Metzler, Pauli Miettinen · 2015

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