מריו בולאי - הפקולטה למדעי המחשב והמידע

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Improving Random Forests by Smoothing, Liu, Z., Luong, P., Boley, M. & Schmidt, D. F., Jul 2026, In: Machine Learning. 115, 7, 152.
Algorithmic iterative reticular synthesis of zeolitic imidazolate framework crystals, Rong, Z., Chen, Z., Luong, F., Chheda, S., Luong, H. T. N., Zheng, Z., Greco, K., Alghamdi, A. A., Bui, K. H., Jaffrelot Inizan, T., Nguyen-Dang, T., Pham, H. H., Le, D. D., Sauer, J., Phung, V. B. T., Chayes, J. T., Borgs, C., Boley, M., El Ghaoui, L. & Yaghi, O. M., Mar 2026, In: Nature Synthesis. 5, 3, p. 409-419 11 p.
Cortical connectivity, local dynamics and stability correlates of global conscious states, Zhao, Y., Tsuchiya, N., Boley, M., Dhanawansa, V., Liu, Y., Karoly, P. J., Pelentritou, A., Woods, W., Liley, D. & Kuhlmann, L., Dec 2025, In: Communications Biology. 8, 1, 1391.
Gradient Boosting Versus Mixed Integer Programming for Sparse Additive Modeling, Yang, F., Le Bodic, P. & Boley, M., 4 Oct 2025, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Proceedings. Ribeiro, R. P., Pfahringer, B., Japkowicz, N., Larrañaga, P., Jorge, A. M., Soares, C., Abreu, P. H. & Gama, J. (eds.). Springer Science and Business Media Deutschland GmbH, p. 453-470 18 p. (Lecture Notes in Computer Science; vol. 16016 LNCS).
Cortical stability and chaos during focal seizures: insights from inference-based modeling, Zhao, Y., Grayden, D. B., Boley, M., Liu, Y., Karoly, P. J., Cook, M. J. & Kuhlmann, L., 1 Jun 2025, In: Journal of Neural Engineering. 22, 3, 036021.
Machine learning outperforms humans in microplastic characterization and reveals human labelling errors in FTIR data, Herb, F., Boley, M. & Fong, W. K., 5 Apr 2025, In: Journal of Hazardous Materials. 487, 136989.
An active machine learning approach for optimal design of magnesium alloys using Bayesian optimisation, Ghorbani, M., Boley, M., Nakashima, P. N. H. & Birbilis, N., Dec 2024, In: Scientific Reports. 14, 1, 8299.
Graph Neural Network-Based Molecular Property Prediction with Patch Aggregation, See, T. J., Zhang, D., Boley, M. & Chalmers, D. K., 22 Oct 2024, In: Journal of Chemical Theory and Computation. 20, 20, p. 8886-8896 11 p.
Roadmap on data-centric materials science, Bauer, S., Benner, P., Bereau, T., Blum, V., Boley, M., Carbogno, C., Catlow, C. A. R., Dehm, G., Eibl, S., Ernstorfer, R., Fekete, Á., Foppa, L., Fratzl, P., Freysoldt, C., Gault, B., Ghiringhelli, L. M., Giri, S. K., Gladyshev, A., Goyal, P. & Hattrick-Simpers, J. & 41 others, Kabalan, L., Karpov, P., Khorrami, M. S., Koch, C. T., Kokott, S., Kosch, T., Kowalec, I., Kremer, K., Leitherer, A., Li, Y., Liebscher, C. H., Logsdail, A. J., Lu, Z., Luong, F., Marek, A., Merz, F., Mianroodi, J. R., Neugebauer, J., Pei, Z., Purcell, T. A. R., Raabe, D., Rampp, M., Rossi, M., Rost, J. M., Saal, J., Saalmann, U., Sasidhar, K. N., Saxena, A., Sbailò, L., Scheidgen, M., Schloz, M., Schmidt, D. F., Teshuva, S., Trunschke, A., Wei, Y., Weikum, G., Xian, R. P., Yao, Y., Yin, J., Zhao, M. & Scheffler, M., Sep 2024, In: Modelling and Simulation in Materials Science and Engineering. 32, 6, 063301.
Inference-based time-resolved chaos analysis of brain models: Application to focal epilepsy, Zhao, Y., Grayden, D. B., Boley, M., Liu, Y., Karoly, P. J., Cook, M. J. & Kuhlmann, L., 2024, FUSION 2024 - 27th International Conference on Information Fusion. Institute of Electrical and Electronics Engineers Inc., (FUSION 2024 - 27th International Conference on Information Fusion).
Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles, Yang, F., Le Bodic, P., Kamp, M. & Boley, M., 2024, In: Proceedings of Machine Learning Research. 238, p. 1117-1125 9 p.
A machine learning approach for accelerated design of magnesium alloys. Part B: Regression and property prediction, Ghorbani, M., Boley, M., Nakashima, P. N. H. & Birbilis, N., Nov 2023, In: Journal of Magnesium and Alloys. 11, 11, p. 4197-4205 9 p.
A machine learning approach for accelerated design of magnesium alloys. Part A: Alloy data and property space, Ghorbani, M., Boley, M., Nakashima, P. N. H. & Birbilis, N., Oct 2023, In: Journal of Magnesium and Alloys. 11, 10, p. 3620-3633 14 p.
Interpretable Machine Learning Models for Phase Prediction in Polymerization-Induced Self-Assembly, Lu, Y., Yalcin, D., Pigram, P. J., Blackman, L. D. & Boley, M., 12 Jun 2023, In: Journal of Chemical Information and Modeling. 63, 11, p. 3288-3306 19 p.
Improved Neurophysiological Process Imaging Through Optimization of Kalman Filter Initial Conditions, Zhao, Y., Luong, F., Teshuva, S., Pelentritou, A., Woods, W., Liley, D., Schmidt, D. F., Boley, M. & Kuhlmann, L., 1 May 2023, In: International Journal of Neural Systems. 33, 5, 2350024.
A Predictive machine-learning model for propagation rate coefficients in radical polymerization, Van de Reydt, E., Marom, N., Saunderson, J., Boley, M. & Junkers, T., 10 Mar 2023, In: Polymer Chemistry. 14, 14, p. 1622-1629 8 p.
Bayes beats Cross Validation: Fast and Accurate Ridge Regression via Expectation Maximization, Tew, S. Y., Boley, M. & Schmidt, D. F., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).
Inference-based time-resolved stability analysis of nonlinear whole-cortex modeling: application to Xenon anaesthesia, Zhao, Y., Boley, M., Pelentritou, A., Woods, W., Liley, D. & Kuhlmann, L., 2023, 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).
Space-time resolved inference-based neurophysiological process imaging: Application to resting-state alpha rhythm, Zhao, Y., Boley, M., Pelentritou, A., Karoly, P. J., Freestone, D. R., Liu, Y., Muthukumaraswamy, S., Woods, W., Liley, D. & Kuhlmann, L., Nov 2022, In: NeuroImage. 263, 119592.
Roadmap on Machine learning in electronic structure, Kulik, H. J., Hammerschmidt, T., Schmidt, J., Botti, S., Marques, M. A. L., Boley, M., Scheffler, M., Todorović, M., Rinke, P., Oses, C., Smolyanyuk, A., Curtarolo, S., Tkatchenko, A., Bartók, A. P., Manzhos, S., Ihara, M., Carrington, T., Behler, J., Isayev, O. & Veit, M. & 27 others, Grisafi, A., Nigam, J., Ceriotti, M., Schütt, K. T., Westermayr, J., Gastegger, M., Maurer, R. J., Kalita, B., Burke, K., Nagai, R., Akashi, R., Sugino, O., Hermann, J., Noé, F., Pilati, S., Draxl, C., Kuban, M., Rigamonti, S., Scheidgen, M., Esters, M., Hicks, D., Toher, C., Balachandran, P. V., Tamblyn, I., Whitelam, S., Bellinger, C. & Ghiringhelli, L. M., 1 Jun 2022, In: Electronic Structure. 4, 2, 023004.
Enhanced Extra Trees Classifier for Epileptic Seizure Prediction, Ntahobari, M., Kuhlmann, L., Boley, M. & Hesabi, Z. R., 2022, 2022 5th International Conference on Signal Processing and Information Security, ICSPIS 2022. Institute of Electrical and Electronics Engineers Inc., p. 175-179 5 p. (2022 5th International Conference on Signal Processing and Information Security, ICSPIS 2022).
Relative Flatness and Generalization, Petzka, H., Kamp, M., Adilova, L., Sminchisescu, C. & Boley, M., 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 18420-18432 13 p. (Advances in Neural Information Processing Systems; vol. 22).
Discovering reliable causal rules, Budhathoki, K., Boley, M. & Vreeken, J., 2021, SIAM International Conference on Data Mining, SDM 2021. Siam Society, p. 1-9 9 p. (SIAM International Conference on Data Mining, SDM 2021).
Identifying domains of applicability of machine learning models for materials science, Sutton, C., Boley, M., Ghiringhelli, L. M., Rupp, M., Vreeken, J. & Scheffler, M., 1 Dec 2020, In: Nature Communications. 11, 1, 4428.
Discovering Functional Dependencies from Mixed-Type Data, Mandros, P., Kaltenpoth, D., Boley, M. & Vreeken, J., 23 Aug 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 1404-1414 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).
Discovering reliable correlations in categorical data, Mandros, P., Boley, M. & Vreeken, J., Nov 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1252-1257 6 p. 8970748. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2019-November).
Discovering robustly connected subgraphs with simple descriptions, Kalofolias, J., Boley, M. & Vreeken, J., Nov 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1150-1155 6 p. 8970683. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2019-November).
Efficiently discovering locally exceptional yet globally representative subgroups, Kalofolias, J., Boley, M. & Vreeken, J., 15 Dec 2017, Proceedings - 17th IEEE International Conference on Data Mining, ICDM 2017. Raghavan, V., Alu, S., Karypis, G., Miele, L. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 197-206 10 p. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2017-November).
Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery, Boley, M., Goldsmith, B. R., Ghiringhelli, L. M. & Vreeken, J., 1 Sep 2017, In: Data Mining and Knowledge Discovery. 31, 5, p. 1391-1418 28 p.
Discovering reliable approximate functional dependencies, Mandros, P., Boley, M. & Vreeken, J., 13 Aug 2017, KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 355-363 9 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; vol. Part F129685).
Uncovering structure-property relationships of materials by subgroup discovery, Goldsmith, B. R., Boley, M., Vreeken, J., Scheffler, M. & Ghiringhelli, L. M., Jan 2017, In: New Journal of Physics. 19, 1, 013031.
Effective parallelisation for machine learning, Kamp, M., Boley, M., Missura, O. & Gärtner, T., 2017, In: Advances in Neural Information Processing Systems. 2017-December, p. 6478-6489 12 p.
Communication-efficient distributed online learning with kernels, Kamp, M., Bothe, S., Boley, M. & Mock, M., 2016, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings. Frasconi, P., Landwehr, N., Manco, G. & Giuseppe, J. (eds.). Springer Verlag, p. 805-819 15 p. (Lecture Notes in Computer Science; vol. 9852 LNAI).
Interesting pattern mining in multi-relational data, Spyropoulou, E., De Bie, T. & Boley, M., May 2014, In: Data Mining and Knowledge Discovery. 28, 3, p. 808-849 42 p.
Communication-efficient distributed online prediction by dynamic model synchronization, Kamp, M., Boley, M., Keren, D., Schuster, A. & Sharfman, I., 2014, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Proceedings. PART 1 ed. Springer Verlag, p. 623-639 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8724 LNAI, no. PART 1).
Instant Exceptional Model Mining using weighted controlled pattern sampling, Moens, S. & Boley, M., 2014, Advances in Intelligent DataAnalysis XIII - 13th International Symposium, IDA 2014, Proceedings. Blockeel, H., van Leeuwen, M. & Vinciotti, V. (eds.). Springer Verlag, p. 203-214 12 p. (Lecture Notes in Computer Science; vol. 8819).
One click mining-interactive local pattern discovery through implicit preference and performance learning, Boley, M., Mampaey, M., Kang, B., Tokmakov, P. & Wrobel, S., 2013, Proceedings of the ACM SIGKDD 2013 Workshop on Interactive Data Exploration and Analytics, IDEA 2013. Association for Computing Machinery, p. 27-35 9 p. (Proceedings of the ACM SIGKDD 2013 Workshop on Interactive Data Exploration and Analytics, IDEA 2013).
Beating human analysts in nowcasting corporate earnings by using publicly available stock price and correlation features, Kamp, M., Boley, M. & Gartner, T., 2013, p. 384-390. 7 p.
Privacy-preserving mobility monitoring using sketches of stationary sensor readings, Kamp, M., Kopp, C., Mock, M., Boley, M. & May, M., 2013, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Proceedings. PART 3 ed. Springer Verlag, p. 370-386 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8190 LNAI, no. PART 3).
Linear space direct pattern sampling using coupling from the past, Boley, M., Moens, S. & Gärtner, T., 2012, KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. p. 69-77 9 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).
Listing closed sets of strongly accessible set systems with applications to data mining, Boley, M., Horváth, T., Poigné, A. & Wrobel, S., 6 Jan 2010, In: Theoretical Computer Science. 411, 3, p. 691-700 10 p.
Subgroup discovery for election analysis: A case study in descriptive data mining, Grosskreutz, H., Boley, M. & Krause-Traudes, M., 2010, Discovery Science - 13th International Conference, DS 2010, Proceedings. p. 57-71 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 6332 LNAI).
Approximating the number of frequent sets in dense data, Boley, M. & Grosskreutz, H., 2009, In: Knowledge and Information Systems. 21, 1, p. 65-89 25 p.
Non-redundant subgroup discovery using a closure system, Boley, M. & Grosskreutz, H., 2009, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2009, Proceedings. PART 1 ed. Springer Verlag, p. 179-194 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5781 LNAI, no. PART 1).
On the complexity of constraint-based theory extraction, Boley, M. & Gärtner, T., 2009, Discovery Science - 12th International Conference, DS 2009, Proceedings. p. 92-106 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5808 LNAI).
Probabilistic structured predictors, Vembu, S., Gärtner, T. & Boley, M., 2009, Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009. AUAI Press, p. 557-564 8 p. (Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009).
Efficient discovery of interesting patterns based on strong closedness, Boley, M., Horváth, T. & Wrobel, S., 2009, Society for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics 133. Society for Industrial and Applied Mathematics Publications, p. 997-1008 12 p. (Society for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics; vol. 2).
A randomized approach for approximating the number of frequent sets, Boley, M. & Grosskreutz, H., 2008, Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008. Institute of Electrical and Electronics Engineers Inc., p. 43-52 10 p. 4781099. (Proceedings - IEEE International Conference on Data Mining, ICDM).
Efficient closed pattern mining in strongly accessible set systems (extended abstract), Boley, M., Horváth, T., Poigné, A. & Wrobel, S., 31 Aug 2007, Knowledge Discovery in Database: PKDD 2007 - 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Proceedings. Springer Verlag, p. 382-389 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 4702 LNAI).
On approximating minimum infrequent and maximum frequent sets, Boley, M., 2007, Discovery Science - 10th International Conference, DS 2007, Proceedings. Springer Verlag, p. 68-77 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 4755 LNAI).

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