Universal Approximation Using Randomly Local Linear Models. - Laurens Bliek (CoRR, 2013)

Exploration and Exploitation in Visuomotor Prediction of Autonomous Agents. - Laurens Bliek (CoRR, 2013)

Online function minimization with convex random relu expansions. - Laurens Bliek; Michel Verhaegen; Sander Wahls (MLSP, 2017)

Online Optimization With Costly and Noisy Measurements Using Random Fourier Expansions. - Laurens Bliek; Hans R. G. W. Verstraete; Michel Verhaegen; Sander Wahls (IEEE Trans. Neural Networks Learn. Syst., 2018)

Automatic tuning of photonic beamformers: A data-driven approach. - Laurens Bliek (2019)

Continuous Surrogate-Based Optimization Algorithms Are Well-Suited for Expensive Discrete Problems. - Rickard Karlsson; Laurens Bliek; Sicco Verwer; Mathijs de Weerdt (BNAIC/BENELEARN (Selected Papers), 2020)

The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search. - Sicco Verwer; Azqa Nadeem; Christian A. Hammerschmidt; Laurens Bliek; Abdullah Al-Dujaili; Una-May O'Reilly (AISec@CCS, 2020)

Black-box Mixed-Variable Optimisation using a Surrogate Model that Satisfies Integer Constraints. - Laurens Bliek; Sicco Verwer; Mathijs de Weerdt (CoRR, 2020)

Hospital simulation model optimisation with a random ReLU expansion surrogate model. - Laurens Bliek; Arthur Guijt; Rickard Karlsson (GECCO Companion, 2021)

Black-box mixed-variable optimisation using a surrogate model that satisfies integer constraints. - Laurens Bliek; Arthur Guijt; Sicco Verwer; Mathijs de Weerdt (GECCO Companion, 2021)

The EURO Meets NeurIPS 2022 Vehicle Routing Competition. - Wouter Kool 001; Laurens Bliek; Danilo Numeroso; Yingqian Zhang 001; Tom Catshoek; Kevin Tierney; Thibaut Vidal; Joaquim A. S. Gromicho (NeurIPS (Competition and Demos), 2021)

Black-box combinatorial optimization using models with integer-valued minima. - Laurens Bliek; Sicco Verwer; Mathijs de Weerdt (Ann. Math. Artif. Intell., 2021)

EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions. - Laurens Bliek; Arthur Guijt; Rickard Karlsson; Sicco Verwer; Mathijs de Weerdt (CoRR, 2021)

The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems. - Laurens Bliek; Paulo da Costa 001; Reza Refaei Afshar; Yingqian Zhang 001; Tom Catshoek; Daniël Vos; Sicco Verwer; Fynn Schmitt-Ulms; André Hottung; Tapan Shah 001; Meinolf Sellmann; Kevin Tierney; et al. (CoRR, 2022)

Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens. - Stefano Teso; Laurens Bliek; Andrea Borghesi; Michele Lombardi 001; Neil Yorke-Smith; Tias Guns; Andrea Passerini (CoRR, 2022)

Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems. - Remco Coppens; Robbert Reijnen; Yingqian Zhang 001; Laurens Bliek; Berend Steenhuisen (CoRR, 2022)

Baseband-Function Placement With Multi-Task Traffic Prediction for 5G Radio Access Networks. - Ligia Maria Moreira Zorello; Laurens Bliek; Sebastian Troia; Tias Guns; Sicco Verwer; Guido Maier (IEEE Trans. Netw. Serv. Manag., 2022)

Digital Twin Applications in Urban Logistics: An Overview. - Abdo Abouelrous; Laurens Bliek; Yingqian Zhang 001 (CoRR, 2023)

The first AI4TSP competition: Learning to solve stochastic routing problems. - Yingqian Zhang 001; Laurens Bliek; Paulo da Costa 001; Reza Refaei Afshar; Robbert Reijnen; Tom Catshoek; Daniël Vos; Sicco Verwer; Fynn Schmitt-Ulms; André Hottung; Tapan Shah 001; Meinolf Sellmann; et al. (Artif. Intell., 2023)

Benchmarking surrogate-based optimisation algorithms on expensive black-box functions. - Laurens Bliek; Arthur Guijt; Rickard Karlsson; Sicco Verwer; Mathijs de Weerdt (Appl. Soft Comput., 2023)

Black-box optimization for anticipated baseband-function placement in 5G networks. - Ligia Maria Moreira Zorello; Laurens Bliek; Sebastian Troia; Guido Maier; Sicco Verwer (Comput. Networks, 2024)

Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration. - Willem van Jaarsveld; Alp Akçay; Laurens Bliek; Paulo da Costa 001; Mathijs de Weerdt; Rik Eshuis; Stella Kapodistria; Uzay Kaymak; Verus Pronk; Geert-Jan van Houtum; Peter Verleijsdonk; Sicco Verwer; et al. (Commit2Data, 2024)

Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks. - Ya Song; Laurens Bliek; Yingqian Zhang 001 (ICAART (3), 2025)

Enhancing Remaining Useful Life Prediction with Ensemble Multi-Term Fourier Graph Neural Networks. - Ya Song; Laurens Bliek; Yaoxin Wu; Yingqian Zhang 001 (Trans. Mach. Learn. Res., 2025)

Reinforcement Learning for Solving the Pricing Problem in Column Generation: Applications to Vehicle Routing. - Abdo Abouelrous; Laurens Bliek; Adriana F. Gabor; Yaoxin Wu; Yingqian Zhang 001 (CoRR, 2025)

Graph Reduction with Unsupervised Learning in Column Generation: A Routing Application. - Abdo Abouelrous; Laurens Bliek; Adriana F. Gabor; Yaoxin Wu; Yingqian Zhang 001 (CoRR, 2025)