Pauli Miettinen
Professor
Professor of Data Science
School of Computing, Faculty of Science, Forestry and Technology
pauli.miettinen@uef.fi | +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
12 items-
Differentially private tree-based redescription mining
Mihelčić, Matej; Miettinen, Pauli. 2023. Data mining and knowledge discovery. 37: 1548-1590 -
Serenade: An Approach for Differentially Private Greedy Redescription Mining
Karjalainen, Maiju; Galbrun, Esther; Miettinen, Pauli. Teoksessa: Goethals, Bart; Robardet, Céline; Siebes, Arno (toim.) , 2023. 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). s. 31-46. CEUR -
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations
Marette, Thibault; Miettinen, Pauli; Neumann, Stefan. Teoksessa: Koutra, Danai; Plant, Claudia; Gomez Rodriguez, Manuel; Baralis; Elena; Bonchi, Francesco(toim.) , 2023. Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part I. s. 743-758. Springer -
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 -
Biclustering and boolean matrix factorization in data streams
Neumann, Stefan; Miettinen, Pauli. Teoksessa: (toim.) , 2020. . s. 1709-1722. -
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 -
Recent developments in boolean matrix factorization
Miettinen Pauli ; Neumann, Stefan. Teoksessa: Bessiere, Christian(toim.) , 2020. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20) Survey track. s. 4922-4928. -
Boolean matrix factorization meets consecutive ones property
Tatti, Nikolaj; Miettinen, Pauli. Teoksessa: Berger-Wolf, Tanya; Chawla, Nitesh(toim.) , 2019. Proceedings of the 2019 SIAM International Conference on Data Mining. s. 729-737. Society for industrial and applied mathematics -
HyGen: generating random graphs with hyperbolic communities
Metzler, Saskia; Miettinen, Pauli. 2019. Applied network science. 4: 53 -
Stability and dynamics of communities on online question-answer sites
Metzler, Saskia; Günnemann, Stephan; Miettinen, Pauli. 2019. Social networks. 58: 50-58