Researcher Portfolio
Dr. Boley, Mario
Databases and Information Systems, MPI for Informatics, Max Planck Society, Theory, Fritz Haber Institute, Max Planck Society
Researcher Profile
Position: Theory, Fritz Haber Institute, Max Planck Society
Position: Databases and Information Systems, MPI for Informatics, Max Planck Society
Researcher ID: https://pure.mpg.de/cone/persons/resource/persons188983
Publications
: Budhathoki, K., Boley, M., & Vreeken, J. (2021). Discovering Reliable Causal Rules. In C. Demeniconi, & I. Davidson (Eds. ), Proceedings of the SIAM International Conference on Data Mining (pp. 1-9). Philadelphis, PA: SIAM. doi:10.1137/1.9781611976700.1. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2020). Discovering Dependencies with Reliable Mutual Information. Knowledge and Information Systems, 62, 4223-4253. doi:10.1007/s10115-020-01494-9. [PubMan] : Sutton, C., Boley, M., Ghiringhelli, L., Rupp, M., Vreeken, J., & Scheffler, M. (2020). Identifying Domains of Applicability of Machine Learning Models for Materials Science. Nature Communications, 11: 4428. doi:10.1038/s41467-020-17112-9. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2019). Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms. In S. Krais (Ed. ), Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (pp. 6206-6210). IJCAI. doi:10.24963/ijcai.2019/864. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2019). Discovering Reliable Correlations in Categorical Data. In 19th IEEE International Conference on Data Mining (pp. 1252-1257). Piscataway, NJ: IEEE. doi: 10.1109/ICDM.2019.00156. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2019). Discovering Reliable Correlations in Categorical Data. Retrieved from http://arxiv.org/abs/1908.11682. [PubMan] : Kalofolias, J., Boley, M., & Vreeken, J. (2019). Discovering Robustly Connected Subgraphs with Simple Descriptions. In 19th IEEE International Conference on Data Mining (pp. 1150-1155). Piscataway, NJ: IEEE. doi:10.1109/ICDM.2019.00139. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2018). Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms. In IEEE International Conference on Data Mining (pp. 317-326). Piscataway, NJ: IEEE. doi:10.1109/ICDM.2018.00047. [PubMan] : Budhathoki, K., Boley, M., & Vreeken, J. (2018). Rule Discovery for Exploratory Causal Reasoning. In Proceedings of the NeurIPS 2018 workshop on Causal Learning. Retrieved from https://drive.google.com/file/d/1r-KTsok3VLIz-wUh0YtsK5YaEu53DcTf/view. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2018). Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms. Retrieved from http://arxiv.org/abs/1809.05467. [PubMan] : Boley, M., Goldsmith, B. R., Ghiringhelli, L. M., & Vreeken, J. (2017). Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery. Data Mining and Knowledge Discovery, 31(5), 1391-1418. doi:10.1007/s10618-017-0520-3. [PubMan] : Goldsmith, B., Boley, M., Vreeken, J., Scheffler, M., & Ghiringhelli, L. M. (2017). Uncovering structure-property relationships of materials by subgroup discovery. New Journal of Physics, 19(1): 013031. doi:10.1088/1367-2630/aa57c2. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2017). Discovering Reliable Approximate Functional Dependencies. Retrieved from http://arxiv.org/abs/1705.09391. [PubMan] : Boley, M., Goldsmith, B. R., Ghiringhelli, L. M., & Vreeken, J. (2017). Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery. Retrieved from http://arxiv.org/abs/1701.07696. [PubMan] : Kalofolias, J., Boley, M., & Vreeken, J. (2017). Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups. Retrieved from http://arxiv.org/abs/1709.07941. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2017). Discovering Reliable Approximate Functional Dependencies. In KDD '17 Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 355-363). [PubMan] : Kamp, M., Boley, M., Missura, O., & Gärtner, T. (2017). Effective Parallelisation for Machine Learning. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, & R. Garnett (Eds. ), Advances in Neural Information Processing Systems 30 (pp. 6477-6488). Curran Associates. [PubMan] : Kalofolias, J., Boley, M., & Vreeken, J. (2017). Efficiently Discovering Locally Exceptional Yet Globally Representative Subgroups. In 17th IEEE International Conference on Data Mining (pp. 197-206). Piscataway, NJ: IEEE. doi:10.1109/ICDM.2017.29. [PubMan] : Goldsmith, B., Boley, M., Vreeken, J., Scheffler, M., & Ghiringhelli, L. (2017). Uncovering Structure-property Relationships of Materials by Subgroup Discovery. New Journal of Physics, 19(1): 013031. doi:10.1088/1367-2630/aa57c2. [PubMan] : Mandros, P., Boley, M., & Vreeken, J. (2017). Discovering Reliable Approximate Functional Dependencies. In KDD'17 (pp. 355-363). New York, NY: ACM. doi:10.1145/3097983.3098062. [PubMan] : Boley, M. (2018). Subgroup Discovery in Materials Science. Talk presented at NOMAD Summer - A hands-on course on tools for novel-materials discovery, CECAM. Lausanne, Switzerland. 2018-09. [PubMan] : Boley, M. (2017). Subgroup Discovery. Talk presented at NOMAD Summer - A hands-on course on tools for novel materials discovery. Berlin, Germany. 2017-09. [PubMan]