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
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
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
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, AM Tyrrell, ...
Artificial Life Conference Proceedings 13, 1056-1063, 2013
Formal modelling and comparing of disaster plans
M Hoogendoorn, CM Jonker, V Popova, A Sharpaskykh, L Xu
Proceedings of the second international conference on information systems …, 2005
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, CN Van Der Wal
International Conference on Industrial, Engineering and Other Applications …, 2011
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
Machine learning for the quantified self
M Hoogendoorn, B Funk
On the art of learning from sensory data, 2018
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
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
Generic parameter control with reinforcement learning
G Karafotias, AE Eiben, M Hoogendoorn
Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014
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
Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks.
M Hoogendoorn
IJCAI 7, 1321-1326, 2007
Modelling the interplay of emotions, beliefs and intentions within collective decision making based on insights from social neuroscience
M Hoogendoorn, J Treur, CN Van Der Wal, A Van Wissen
International Conference on Neural Information Processing, 196-206, 2010
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
Modeling dynamics of relative trust of competitive information agents
M Hoogendoorn, SW Jaffry, J Treur
International Workshop on Cooperative Information Agents, 55-70, 2008
Attentive group equivariant convolutional networks
D Romero, E Bekkers, J Tomczak, M Hoogendoorn
International Conference on Machine Learning, 8188-8199, 2020
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