20072018
If you made any changes in Pure these will be visible here soon.

Personal profile

Research interests

I work on advancing tools for human-centred data analysis. In contrast to machine learning methods that aim for automation (e.g., self-driving cars), human-centred data analysis methods aim to empower human users. In order to be effective, such methods and their results must be simple and interpretable yet provide valid answers to critical analysis questions.

I am interested in all aspects of data analysis methods: learning-theoretic foundations, efficient algorithms, and concrete applications. For the latter, I particularly focus on supporting scientific discoveries. For example, I collaborate with materials science researchers to pursue the data-driven discovery of novel functional materials.

Research area keywords

  • Data Science
  • Data analysis
  • Machine Learning
  • Data mining

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2007 2018

1 Citation (Scopus)

Discovering reliable dependencies from data: hardness and improved algorithms

Mandros, P., Boley, M. & Vreeken, J., 2018, Proceedings - 18th IEEE International Conference on Data Mining Workshops, ICDM 2018: 17–20 November 2018 Singapore. Tao, D. & Thuraisingham, B. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 317-326 10 p. 8594856

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Rule discovery for exploratory causal reasoning

Budhathoki, K., Boley, M. & Vreeken, J., 2018, NeurIPS 2018 Workshop on Causal Learning. Arjovsky, M., Heinze-Deml, C., Klimovskaia, A., Oquab, M., Bottou, L. & Lopez-Paz, D. (eds.). Neural Information Processing Systems Foundation Inc., 14 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Open Access
File
11 Citations (Scopus)

Discovering reliable approximate functional dependencies

Mandros, P., Boley, M. & Vreeken, J., 2017, KDD'17 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining: August 13-17, 2017 Halifax, NS, Canada. Rosales, R. (ed.). New York NY USA: Association for Computing Machinery (ACM), p. 355-363 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Effective parallelisation for machine learning

Kamp, M., Boley, M., Missura, O. & Gärtner, T., 2017, NIPS Proceedings: Advances in Neural Information Processing Systems (NIPS 2017). Guyon, I., Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R. & Vishwanathan, S. (eds.). San Deigo CA USA: Neural Information Processing Systems Foundation Inc., 22 p. (Advances in Neural Information Processing Systems; no. 30).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Efficiently discovering locally exceptional yet globally representative subgroups

Kalofolias, J., Boley, M. & Vreeken, J., 2017, Proceedings - 17th IEEE International Conference on Data Mining, ICDM 2017: 18–21 November 2017 New Orleans, Louisiana. Raghavan, V., Alu, S., Karypis, G., Miele, L. & Wu, X. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 197-206 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Prizes

Best-Paper-Award ICDM 2018

Panagiotis Mandros (Recipient), Mario Boley (Recipient) & Jilles Vreeken (Recipient), 2018

Prize: Prize (including medals and awards)

Best-Student-Paper-Award ICDM 2008

Mario Boley (Recipient) & Henrik Grosskreutz (Recipient), 2008

Prize: Prize (including medals and awards)