| A survey on filter techniques for feature selection in gene expression microarray analysis C Lazar, J Taminau, S Meganck, D Steenhoff, A Coletta, C Molter, ... IEEE/ACM transactions on computational biology and bioinformatics 9 (4 …, 2012 | 689 | 2012 |
| Multi-objective reinforcement learning using sets of pareto dominating policies K Van Moffaert, A Nowé The Journal of Machine Learning Research 15 (1), 3483-3512, 2014 | 400 | 2014 |
| Batch effect removal methods for microarray gene expression data integration: a survey C Lazar, S Meganck, J Taminau, D Steenhoff, A Coletta, C Molter, ... Briefings in bioinformatics 14 (4), 469-490, 2013 | 373 | 2013 |
| A practical guide to multi-objective reinforcement learning and planning CF Hayes, R Rădulescu, E Bargiacchi, J Källström, M Macfarlane, ... Autonomous Agents and Multi-Agent Systems 36 (1), 26, 2022 | 361 | 2022 |
| NRGcoin: Virtual currency for trading of renewable energy in smart grids M Mihaylov, S Jurado, N Avellana, K Van Moffaert, IM de Abril, A Nowé 11th International conference on the European energy market (EEM14), 1-6, 2014 | 342 | 2014 |
| Game theory and multi-agent reinforcement learning A Nowé, P Vrancx, YM De Hauwere Reinforcement Learning: State-of-the-Art, 441-470, 2012 | 312 | 2012 |
| Scalarized multi-objective reinforcement learning: Novel design techniques K Van Moffaert, MM Drugan, A Nowé 2013 IEEE symposium on adaptive dynamic programming and reinforcement …, 2013 | 303 | 2013 |
| Reinforcement learning from demonstration through shaping T Brys, A Harutyunyan, HB Suay, S Chernova, ME Taylor, A Nowé Twenty-fourth international joint conference on artificial intelligence, 2015 | 297 | 2015 |
| Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages J Taminau, S Meganck, C Lazar, D Steenhoff, A Coletta, C Molter, ... BMC bioinformatics 13, 1-9, 2012 | 199 | 2012 |
| Dynamic weights in multi-objective deep reinforcement learning A Abels, D Roijers, T Lenaerts, A Nowé, D Steckelmacher International conference on machine learning, 11-20, 2019 | 196 | 2019 |
| Designing multi-objective multi-armed bandits algorithms: A study MM Drugan, A Nowe The 2013 international joint conference on neural networks (IJCNN), 1-8, 2013 | 174 | 2013 |
| Evolutionary game theory and multi-agent reinforcement learning K Tuyls, A Nowé The Knowledge Engineering Review 20 (1), 63-90, 2005 | 166 | 2005 |
| Multi-objective multi-agent decision making: a utility-based analysis and survey R Rădulescu, P Mannion, DM Roijers, A Nowé Autonomous Agents and Multi-Agent Systems 34 (1), 10, 2020 | 162 | 2020 |
| Expressing arbitrary reward functions as potential-based advice A Harutyunyan, S Devlin, P Vrancx, A Nowé Proceedings of the AAAI conference on artificial intelligence 29 (1), 2015 | 131 | 2015 |
| Distilling deep reinforcement learning policies in soft decision trees Y Coppens, K Efthymiadis, T Lenaerts, A Nowé, T Miller, R Weber, ... Proceedings of the IJCAI 2019 workshop on explainable artificial …, 2019 | 130 | 2019 |
| Reviewing machine learning of corrosion prediction in a data-oriented perspective LB Coelho, D Zhang, Y Van Ingelgem, D Steckelmacher, A Nowé, ... npj Materials Degradation 6 (1), 8, 2022 | 118 | 2022 |
| Predicting disease-causing variant combinations S Papadimitriou, A Gazzo, N Versbraegen, C Nachtegael, J Aerts, ... Proceedings of the National Academy of Sciences 116 (24), 11878-11887, 2019 | 114 | 2019 |
| Two-step particle swarm optimization to solve the feature selection problem R Bello, Y Gomez, A Nowe, MM Garcia Seventh international conference on intelligent systems design and …, 2007 | 113 | 2007 |
| Policy Transfer using Reward Shaping. T Brys, A Harutyunyan, ME Taylor, A Nowé AAMAS, 181-188, 2015 | 110 | 2015 |
| Model-predictive control and reinforcement learning in multi-energy system case studies G Ceusters, RC Rodríguez, AB García, R Franke, G Deconinck, L Helsen, ... Applied Energy 303, 117634, 2021 | 104 | 2021 |
Peter VrancxPrincipal Researcher at IMEC在 imec.be 的电子邮件经过验证
