Publications

  • Karel, J., & Peeters, R. (2018). Orthogonal Matched Wavelets with Vanishing Moments: A Sparsity Design Approach. Circuits Systems and Signal Processing, 37(8), 3487-3514. DOI: 10.1007/s00034-017-0716-1
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  • Uiterwijk, JWHM. (2018). Construction and Investigation of Cram Endgame Databases. In Proceedings of the 10th International Conference on Computers and Games New Taipei City: National Taipei University.
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  • Baier, H., & Winands, M. H. M. (2018). MCTS-Minimax Hybrids with State Evaluations (Extended Abstract). 5548-5552. Paper presented at Twenty-Seventh International Joint Conference on Artificial Intelligence, Stockholm, Sweden.DOI: 10.24963/ijcai.2018/782
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  • Gaina, R. D., Couëtoux, A., Soemers, D. J. N. J., Winands, M. H. M., Vodopivec, T., Kirchgessner, F., ... Diego Perez-Liebana, D. (2018). The 2016 Two-Player GVGAI Competition. IEEE Transactions on Games, 10(2), 209-220. DOI: 10.1109/TCIAIG.2017.2771241
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  • Baier, H., & Winands, M. H. M. (2018). MCTS-Minimax Hybrids with State Evaluations. Journal of Artificial Intelligence Research, 62, 193-231. DOI: 10.1613/jair.1.11208
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  • Cluitmans, M., Karel, J., Bonizzi, P., Volders, P., Westra, R., & Peeters, R. (2018). Wavelet-promoted sparsity for non-invasive reconstruction of electrical activity of the heart. Medical & Biological Engineering & Computing. DOI: 10.1007/s11517-018-1831-2
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  • Böhmová, K., Häfliger, L., Mihalák, M., Pröger, T., Sacomoto, G., & Sagot, M-F. (2018). Computing and Listing st-Paths in Public Transportation Networks. Theory of Computing Systems, 62(3), 600-621. DOI: 10.1007/s00224-016-9747-4
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  • Hertroijs, D. FL., Elissen, A. MJ., Brouwers, M. CGJ., Schaper, N. C., Köhler, S., Popa, M. C., ... Ruwaard, D. (2018). A risk score including body mass index, glycated haemoglobin and triglycerides predicts future glycaemic control in people with type 2 diabetes. Diabetes, Obesity and Metabolism, 20(3), 681-688. DOI: 10.1111/dom.13148
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  • Javier Muros, F., M. Maestre , J., You, L., & Stankova, K. (2018). Model predictive control for optimal treatment in a spatial cancer game. In Proceedings of the 2017 IEEE 56th Annual Conference on Decision and Control (CDC) (Vol. 56, pp. 5539 - 5544 ). Melbourne, VIC, Australia: IEEE. DOI: 10.1109/CDC.2017.8264481
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  • Krebs, F., Lubascher, B., Moers, T., Schaap, P., & Spanakis, G. (2018). Social Emotion Mining Techniques for Facebook Posts Reaction Prediction. In Proceedings of the 10th International Conference on Agents and Artificial Intelligence (pp. 211-220). DOI: 10.5220/0006656002110220
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  • Soemers, D. J. N. J., Brys, T., Driessens, K., Winands, M. H. M., & Nowé, A. (2018). Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2-7, 2018: The Thirtieth AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-18) (pp. 7831-7836). AAAI Press.
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  • Davarzani, N. (2018). Biomarker discovery in heart failure Maastricht: Maastricht University DOI: 10.26481/dis.20180702nd
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  • Sun, Z., & Roos, N. (2018). Dynamically stable walk control of biped humanoid on uneven and inclined terrain. Neurocomputing, 280, 111 - 122. DOI: 10.1016/j.neucom.2017.08.077
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  • Roos, N. (2018). Learning-Based Diagnosis and Repair. In B. Verheij, & M. Wiering (Eds.), Artificial Intelligence: 29th Benelux Conference, BNAIC 2017, Groningen, The Netherlands, November 8–9, 2017, Revised Selected Papers (pp. 1-15). (Communications in Computer and Information Science; Vol. 823). Cham: Springer International Publishing.
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  • Sironi, C. F., & Winands, M. H. M. (2018). On-Line Parameter Tuning for Monte-Carlo Tree Search in General Game Playing. In T. Cazenave, M. H. M. Winands, & A. Saffidine (Eds.), Computer Games: 6th Workshop, CGW 2017, Held in Conjunction with the 26th International Conference on Artificial Intelligence, IJCAI 2017, Melbourne, VIC, Australia, August, 20, 2017, Revised Selected Papers (pp. 75-95). Cham: Springer International Publishing. DOI: 10.1007/978-3-319-75931-9_6
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  • Buhmann, J. M., Gronskiy, A. Y., Mihalák, M., Pröger, T., Šrámek, R., & Widmayer, P. (2018). Robust optimization in the presence of uncertainty: A generic approach. Journal of Computer and System Sciences, 94, 135-166. DOI: 10.1016/j.jcss.2017.10.004
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  • Sironi, C. F., Liu, J., Perez-Liebana, D., Gaina, R. D., Bravi, I., Lucas, S. M., & Winands, M. H. M. (2018). Self-adaptive MCTS for General Video Game Playing. In K. Sim, & P. Kaufmann (Eds.), Applications of Evolutionary Computation. EvoApplications 2018 (Vol. 10784, pp. 358-375). (Lecture Notes in Computer Science; Vol. 10784). Springer. DOI: 10.1007/978-3-319-77538-8_25
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  • Schüller, K., Stankova, K., You, L., & Thuijsman, F. (2018). Simulations of Complex Evolutionary Games. Poster session presented at Understanding Cancer Through Evolutionary Game Theory, Leiden, Netherlands.
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  • You, L. (2018). Spatial and nonspatial evolutionary games and their applications Maastricht: Maastricht University DOI: 10.26481/dis.20180207yl
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  • You, L., Brown, J. S., Thuijsman, F., Cunningham, J. J., Gatenby, R. A., Zhang, J., & Stankova, K. (2017). Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model. Journal of Theoretical Biology, 435, 78-97. DOI: 10.1016/j.jtbi.2017.08.022
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