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ORCIDLaurens Bliek
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- affiliation: Eindhoven University of Technology, The Netherlands
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Books and Theses
- 2019
[b1]Laurens Bliek:
Automatic tuning of photonic beamformers: A data-driven approach. Delft University of Technology, Netherlands, 2019
Journal Articles
- 2024
- [j6]Ligia Maria Moreira Zorello, Laurens Bliek
, Sebastian Troia, Guido Maier, Sicco Verwer:
Black-box optimization for anticipated baseband-function placement in 5G networks. Comput. Networks 245: 110384 (2024) - 2023
- [j5]Yingqian Zhang, Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Robbert Reijnen, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The first AI4TSP competition: Learning to solve stochastic routing problems. Artif. Intell. 319: 103918 (2023) - [j4]Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt:
Benchmarking surrogate-based optimisation algorithms on expensive black-box functions. Appl. Soft Comput. 147: 110744 (2023) - 2022
- [j3]Ligia Maria Moreira Zorello, Laurens Bliek, Sebastian Troia, Tias Guns, Sicco Verwer, Guido Maier:
Baseband-Function Placement With Multi-Task Traffic Prediction for 5G Radio Access Networks. IEEE Trans. Netw. Serv. Manag. 19(4): 5104-5119 (2022) - 2021
- [j2]Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Black-box combinatorial optimization using models with integer-valued minima. Ann. Math. Artif. Intell. 89(7): 639-653 (2021) - 2018
- [j1]Laurens Bliek, Hans R. G. W. Verstraete, Michel Verhaegen, Sander Wahls:
Online Optimization With Costly and Noisy Measurements Using Random Fourier Expansions. IEEE Trans. Neural Networks Learn. Syst. 29(1): 167-182 (2018)
Conference and Workshop Papers
- 2021
- [c6]Laurens Bliek, Arthur Guijt, Rickard Karlsson:
Hospital simulation model optimisation with a random ReLU expansion surrogate model. GECCO Companion 2021: 13-14 - [c5]Laurens Bliek, Arthur Guijt, Sicco Verwer, Mathijs de Weerdt:
Black-box mixed-variable optimisation using a surrogate model that satisfies integer constraints. GECCO Companion 2021: 1851-1859 - [c4]Wouter Kool, Laurens Bliek, Danilo Numeroso, Yingqian Zhang, Tom Catshoek, Kevin Tierney, Thibaut Vidal, Joaquim A. S. Gromicho:
The EURO Meets NeurIPS 2022 Vehicle Routing Competition. NeurIPS (Competition and Demos) 2021: 35-49 - 2020
- [c3]Rickard Karlsson, Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Continuous Surrogate-Based Optimization Algorithms Are Well-Suited for Expensive Discrete Problems. BNAIC/BENELEARN (Selected Papers) 2020: 48-63 - [c2]Sicco Verwer, Azqa Nadeem, Christian A. Hammerschmidt, Laurens Bliek, Abdullah Al-Dujaili, Una-May O'Reilly:
The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search. AISec@CCS 2020: 61-70 - 2017
- [c1]Laurens Bliek, Michel Verhaegen, Sander Wahls:
Online function minimization with convex random relu expansions. MLSP 2017: 1-6
Parts in Books or Collections
- 2024
- [p1]Willem van Jaarsveld, Alp Akçay, Laurens Bliek, Paulo da Costa, Mathijs de Weerdt, Rik Eshuis, Stella Kapodistria, Uzay Kaymak, Verus Pronk, Geert-Jan van Houtum, Peter Verleijsdonk, Sicco Verwer, Simon Voorberg, Yingqian Zhang:
Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration. Commit2Data 2024: 5:1-5:13
Informal and Other Publications
- 2023
- [i12]Abdo Abouelrous, Laurens Bliek, Yingqian Zhang:
Digital Twin Applications in Urban Logistics: An Overview. CoRR abs/2302.00484 (2023) - [i11]Ya Song, Laurens Bliek, Yingqian Zhang:
Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks. CoRR abs/2302.04035 (2023) - 2022
- [i10]Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Yingqian Zhang, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems. CoRR abs/2201.10453 (2022) - [i9]Stefano Teso, Laurens Bliek, Andrea Borghesi, Michele Lombardi, Neil Yorke-Smith, Tias Guns, Andrea Passerini:
Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens. CoRR abs/2205.10157 (2022) - [i8]Remco Coppens, Robbert Reijnen, Yingqian Zhang, Laurens Bliek, Berend Steenhuisen:
Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems. CoRR abs/2211.09719 (2022) - 2021
- [i7]Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt:
EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions. CoRR abs/2106.04618 (2021) - 2020
- [i6]Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Black-box Mixed-Variable Optimisation using a Surrogate Model that Satisfies Integer Constraints. CoRR abs/2006.04508 (2020) - [i5]Rickard Karlsson, Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Continuous surrogate-based optimization algorithms are well-suited for expensive discrete problems. CoRR abs/2011.03431 (2020) - 2019
- [i4]Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Black-box Combinatorial Optimization using Models with Integer-valued Minima. CoRR abs/1911.08817 (2019) - 2016
- [i3]Laurens Bliek, Hans R. G. W. Verstraete, Michel Verhaegen, Sander Wahls:
Online Optimization with Costly and Noisy Measurements using Random Fourier Expansions. CoRR abs/1603.09620 (2016) - 2013
- [i2]Laurens Bliek:
Universal Approximation Using Randomly Local Linear Models. CoRR abs/1308.6498 (2013) - [i1]Laurens Bliek:
Exploration and Exploitation in Visuomotor Prediction of Autonomous Agents. CoRR abs/1309.7959 (2013)
Coauthor Index
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