Mark Hoogendoorn
Mark Hoogendoorn
Full Professor of Artificial Intelligence, VU University Amsterdam
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Parameter control in evolutionary algorithms: Trends and challenges
G Karafotias, M Hoogendoorn, ÁE Eiben
IEEE Transactions on Evolutionary Computation 19 (2), 167-187, 2014
Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy
LM Fleuren, TLT Klausch, CL Zwager, LJ Schoonmade, T Guo, ...
Intensive care medicine 46 (3), 383-400, 2020
Modelling collective decision making in groups and crowds: Integrating social contagion and interacting emotions, beliefs and intentions
T Bosse, M Hoogendoorn, MCA Klein, J Treur, CN Van Der Wal, ...
Autonomous Agents and Multi-Agent Systems 27 (1), 52-84, 2013
Modeling centralized organization of organizational change
M Hoogendoorn, CM Jonker, MC Schut, J Treur
Computational and Mathematical Organization Theory 13 (2), 147-184, 2007
The triangle of life: Evolving robots in real-time and real-space
AE Eiben, N Bredeche, M Hoogendoorn, J Stradner, J Timmis, A Tyrrell, ...
European Conference on Artificial Life (ECAL-2013), 1-8, 2013
Formal modelling and comparing of disaster plans
M Hoogedoorn, C Jonker, V Popova, A Sharpanskykh, L Xu
Machine learning for the quantified self
M Hoogendoorn, B Funk
On the art of learning from sensory data, 2018
Modeling situation awareness in human-like agents using mental models
M Hoogendoorn, RM van Lambalgen, J Treur
Twenty-Second International Joint Conference on Artificial Intelligence, 2011
Modeling the Dynamics of Mood and Depression.
F Both, M Hoogendoorn, MCA Klein, J Treur
ECAI, 266-270, 2008
Agent-based analysis of patterns in crowd behaviour involving contagion of mental states
T Bosse, M Hoogendoorn, MCA Klein, J Treur, C Wal
International Conference on Industrial, Engineering and Other Applications …, 2011
Predictive modeling of colorectal cancer using a dedicated pre-processing pipeline on routine electronic medical records
R Kop, M Hoogendoorn, A Ten Teije, FL Büchner, P Slottje, LMG Moons, ...
Computers in biology and medicine 76, 30-38, 2016
Generic parameter control with reinforcement learning
G Karafotias, AE Eiben, M Hoogendoorn
Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014
Attentive group equivariant convolutional networks
D Romero, E Bekkers, J Tomczak, M Hoogendoorn
International Conference on Machine Learning, 8188-8199, 2020
Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer
M Hoogendoorn, P Szolovits, LMG Moons, ME Numans
Artificial intelligence in medicine 69, 53-61, 2016
Predicting social anxiety treatment outcome based on therapeutic email conversations
M Hoogendoorn, T Berger, A Schulz, T Stolz, P Szolovits
IEEE journal of biomedical and health informatics 21 (5), 1449-1459, 2016
Prediction using patient comparison vs. modeling: a case study for mortality prediction
M Hoogendoorn, A El Hassouni, K Mok, M Ghassemi, P Szolovits
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
Modelling the interplay of emotions, beliefs and intentions within collective decision making based on insights from social neuroscience
M Hoogendoorn, J Treur, C Wal, A Wissen
International Conference on Neural Information Processing, 196-206, 2010
Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks.
M Hoogendoorn
IJCAI 7, 1321-1326, 2007
Deep learning-based energy disaggregation and on/off detection of household appliances
J Jiang, Q Kong, MD Plumbley, N Gilbert, M Hoogendoorn, DM Roijers
ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (3), 1-21, 2021
An agent-based model for the interplay of information and emotion in social diffusion
M Hoogendoorn, J Treur, CN van der Wal, A van Wissen
2010 IEEE/WIC/ACM International Conference on Web Intelligence and …, 2010
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