Initialization of big data clustering using distributionally balanced folding. - Joonas Hämäläinen; Tommi Kärkkäinen (ESANN, 2016)

Feature Ranking of Large, Robust, and Weighted Clustering Result. - Mirka Saarela; Joonas Hämäläinen; Tommi Kärkkäinen (PAKDD (1), 2017)

Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering. - Joonas Hämäläinen; Susanne Jauhiainen; Tommi Kärkkäinen (Algorithms, 2017)

Scalable robust clustering method for large and sparse data. - Joonas Hämäläinen; Tommi Kärkkäinen; Tuomo Rossi (ESANN, 2018)

Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection. - Joonas Hämäläinen; Alisson S. C. Alencar; Tommi Kärkkäinen; César L. C. Mattos; Amauri H. Souza Júnior; João P. P. Gomes (CoRR, 2019)

Problem Transformation Methods with Distance-Based Learning for Multi-Target Regression. - Joonas Hämäläinen; Tommi Kärkkäinen (ESANN, 2020)

Scalable Initialization Methods for Large-Scale Clustering. - Joonas Hämäläinen; Tommi Kärkkäinen; Tuomo Rossi (CoRR, 2020)

Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine? - Joakim Linja; Joonas Hämäläinen; Paavo Nieminen; Tommi Kärkkäinen (Mach. Learn. Knowl. Extr., 2020)

Instance-Based Multi-Label Classification via Multi-Target Distance Regression. - Joonas Hämäläinen; Paavo Nieminen; Tommi Kärkkäinen (ESANN, 2021)

Orientation Adaptive Minimal Learning Machine for Directions of Atomic Forces. - Antti Pihlajamäki; Joakim Linja; Joonas Hämäläinen; Paavo Nieminen; Sami Malola; Tommi Kärkkäinen; Hannu Häkkinen (ESANN, 2021)

Improving Scalable K-Means++. - Joonas Hämäläinen; Tommi Kärkkäinen; Tuomo Rossi (Algorithms, 2021)

Feature Selection for Multi-label Classification with Minimal Learning Machine. - Joakim Linja; Joonas Hämäläinen; Tommi Kärkkäinen (ESANN, 2023)

Knowledge Discovery from Atomic Structures using Feature Importances. - Joakim Linja; Joonas Hämäläinen; Antti Pihlajamäki; Paavo Nieminen; Sami Malola; Hannu Häkkinen; Tommi Kärkkäinen (CoRR, 2023)

Minimal Learning Machine for Multi-Label Learning. - Joonas Hämäläinen; Amauri H. de Souza; César L. C. Mattos; João P. P. Gomes; Tommi Kärkkäinen (CoRR, 2023)

Mapping the Challenges of HCI: An Application and Evaluation of ChatGPT and GPT-4 for Cost-Efficient Question Answering. - Jonas Oppenlaender; Joonas Hämäläinen (CoRR, 2023)

Feature selection for distance-based regression: An umbrella review and a one-shot wrapper. - Joakim Linja; Joonas Hämäläinen; Paavo Nieminen; Tommi Kärkkäinen (Neurocomputing, 2023)

Containers as the Quantum Leap in Software Development. - Iftikhar Ahmad; Teemu Autto; Teerath Das; Joonas Hämäläinen; Pasi Jalonen; Viljami Järvinen; Harri Kallio; Tomi Kankainen; Taija Kolehmainen; Pertti Kontio; Pyry Kotilainen; Matti Kurittu; et al. (CoRR, 2025)

A Systematic Literature Review of Multi-Label Learning in Software Engineering. - Joonas Hämäläinen; Teerath Das; Tommi Mikkonen (ACM Trans. Softw. Eng. Methodol., 2025)