Research Output per year
Research Output per year
Personal profile
Research profile
Paulo R. de O. da Costa currently pursues a PhD at the Eindhoven University of Technology, The Netherlands, on the topic of Real-time Data-driven Maintenance Logistics. His current research interests are related to using Machine Learning and Optimisation methods applied to sequential decision-making problems.
Academic background
Paulo R. de O. da Costa, MSc. is pursuing a PhD at the School of Industrial Engineering and Innovation Sciences in the Information Systems Group at the Eindhoven University of Technology. He holds a BSc in Computational and Applied Mathematics from the University of Campinas (Unicamp) in Brazil and an MSc in Business Analytics from University College Dublin (UCD) in Ireland.
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Research Output
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Data-Driven Policy on Feasibility Determination for the Train Shunting Problem
De Oliveira Da Costa, P., Rhuggenaath, J., Zhang, Y., Akcay, A., Lee, W-J. & Kaymak, U., 30 Apr 2020, The European Conference on Machine Learning and Principles (ECML2019) and Practice of Knowledge Discovery in Databases (PKDD2019). Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M. & Robardet, C. (eds.). Berlin: Springer, p. 719-734 16 p. (Lecture Notes in Artificial Intelligence; vol. 11908 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile -
Dynamic pricing using Thompson Sampling with fuzzy events
Rhuggenaath, J., de O. da Costa, P. R., Zhang, Y., Akcay, A. & Kaymak, U., 15 Jun 2020, Information Processing and Management of Uncertainty in Knowledge-Based Systems - 18th International Conference, IPMU 2020, Proceedings. Lesot, M-J., Vieira, S., Reformat, M. Z., Carvalho, J. P., Wilbik, A., Bouchon-Meunier, B. & Yager, R. R. (eds.). p. 653-666 14 p. (Communications in Computer and Information Science; vol. 1237 CCIS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile -
Learning 2-opt heuristics for the traveling salesman problem via deep reinforcement learning
da Costa, P. R. D. O., Rhuggenaath, J., Zhang, Y. & Akcay, A., 3 Apr 2020.Research output: Working paper › Academic
Open AccessFile131 Downloads (Pure) -
Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
de O. da Costa, P. R., Rhuggenaath, J., Zhang, Y. & Akcay, A., 2020, Proceedings of The 12th Asian Conference on Machine Learning. PMLR, p. 465-480 (Proceedings of Machine Learning Research; vol. 129).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access -
Low-regret algorithms for strategic buyers with unknown valuations in repeated posted-price auctions
Rhuggenaath, J., de O. da Costa, P. R., Zhang, Y., Akcay, A. & Kaymak, U., 2020, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 16 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile13 Downloads (Pure)