activity
20162022
collaborators

5 papers

cs.DB2022

Differentially Private Tree-Based Redescription Mining

Matej Mihelčić, Pauli Miettinen

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 sp…

cs.LG2022

Finding Rule-Interpretable Non-Negative Data Representation

Matej Mihelčić, Pauli Miettinen

Non-negative Matrix Factorization (NMF) is an intensively used technique for obtaining parts-based, lower dimensional and non-negative representation. Researchers in biology, medic…

cs.LG2020

Approaches For Multi-View Redescription Mining

Matej Mihelčić, Tomislav Šmuc

The task of redescription mining explores ways to re-describe different subsets of entities contained in a dataset and to reveal non-trivial associations between different subsets…

q-bio.QM2017

Using Redescription Mining to Relate Clinical and Biological Characteristics of Cognitively Impaired and Alzheimer's Disease Patients

Matej Mihelčić, Goran Šimić, Mirjana Babić Leko +3

We used redescription mining to find interpretable rules revealing associations between those determinants that provide insights about the Alzheimer's disease (AD). We extended the…

cs.AI2016

A framework for redescription set construction

Matej Mihelčić, Sašo Džeroski, Nada Lavrač +1

Redescription mining is a field of knowledge discovery that aims at finding different descriptions of similar subsets of instances in the data. These descriptions are represented a…