Pauli Miettinen
Professor
Professor of Data Science
School of Computing, Faculty of Science, Forestry and Technology
[email protected] | +358 50 475 3210
My research covers data science from method development to applications. The most important fields I have developed methods for are matrix and tensor decompositions over non-standard algebras, redescription mining, and analysis of social networks. Their applications range from data mining, ecological niche modelling, the analysis of parliamentary candidates’ opinions, and the analysis of voluntary-based network services to health data analysis.
For more information, please see my home page (link at the end of the page).
Research groups
Projects
Publications
15/15 items-
Finding Rule-Interpretable Non-Negative Data Representation
Mihelčić, Matej; Miettinen, Pauli, 2025, IEEE transactions on knowledge and data engineering, 37, 5, 2538-2549. A1 Journal article (refereed), original research -
Fast Redescription Mining Using Locality-Sensitive Hashing
Karjalainen, Maiju; Galbrun, Esther; Miettinen, Pauli, 2024, Bifet, Albert; Davis, Jesse; Krilavičius, Tomas; Kull, Meelis; Ntoutsi, Eirini; Žliobaitė, Indrė, Machine Learning and Knowledge Discovery in Databases: Research Track. European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part VII, 124-142. A4 Conference proceedings -
Työpaikan kemialliset, biologiset ja fysikaaliset altisteet: kyselyn avovastausten tietokoneavusteinen analyysi
Miettinen, Pauli; Pope, Paul; Pääkkönen, Rauno; Kyrkkö, Kirsi; Orsila, Reetta; Teronen, Arto; Pasanen, Pertti, 2024, Itä-Suomen yliopisto. D4 Published development or research report or study -
Differentially private tree-based redescription mining
Mihelčić, Matej; Miettinen, Pauli, 2023, Data mining and knowledge discovery, 37, 4, 1548-1590. A1 Journal article (refereed), original research -
Serenade: An Approach for Differentially Private Greedy Redescription Mining
Karjalainen, Maiju; Galbrun, Esther; Miettinen, Pauli, 2023, Goethals, Bart; Robardet, Céline; Siebes, Arno , KDID 2022 Knowledge Discovery in Inductive Databases 2022 : Proceedings of the 20th anniversary Workshop on Knowledge Discovery in Inductive Databases co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2022 (ECMLPKDD 2022), 31-46. A4 Conference proceedings -
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations
Marette, Thibault; Miettinen, Pauli; Neumann, Stefan, 2023, Koutra, Danai; Plant, Claudia; Gomez Rodriguez, Manuel; Baralis; Elena; Bonchi, Francesco, Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part I, 743-758. A4 Conference proceedings -
Proceedings: 21st IEEE International Conference on Data Mining. 7-10 December 2021. Virtual Conference
Bailey, James; Miettinen, Pauli; Koh, Yun Sing; Tao, Dacheng; Wu, Xindong, 2021, IEEE. C2 Edited book, conference proceedings or special issue of a journal -
Biclustering and boolean matrix factorization in data streams
Neumann, Stefan; Miettinen, Pauli, 2020, 1709-1722, International Conference on Very Large Data Bases. A4 Conference proceedings -
Lainvalmistelu tiedonhallinnan haasteena - tekoäly ratkaisuna?
Lonka, Harriet; Keinänen, Anssi; Ovaska, Eeva; Kiiski, Kimmo; Jääskinen, Niilo; Ylipaavalniemi, Jarkko; Miettinen, Pauli, 2020, Edilex, 2020/17, 1-24. A1 Journal article (refereed), original research -
Recent developments in boolean matrix factorization
Miettinen Pauli ; Neumann, Stefan, 2020, Bessiere, Christian, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20) Survey track, 4922-4928. A4 Conference proceedings