Mark Hoogendoorn
researcher
Facts
8 properties- Instance of
- human
- Occupation
- researcher, computer scientist
- Educated at
- Vrije Universiteit Amsterdam[3]
- Doctoral advisor
- Catholijn Jonker, Jan Treur[4][5]
- Family name
- Hoogendoorn[7]
- Maintained by WikiProject
- WikiProject Mathematics[9]
🏷️ Also known as
en Mark Hoogendoorn
🔖 Identifiers · 12
- ORCID iD
- 0000-0003-3356-3574
- VIAF cluster ID
- 306106513
- Library of Congress authority ID
- nb2013013241
- GND ID
- 1174019808
- DDB person (GND) ID
- 1174019808
- IdRef ID
- 25406678X
- MR Author ID
- 924672
- Mathematics Genealogy Project ID
- 115817
- National Library of Israel J9U ID
- 987007357723605171
- Nationale Thesaurus voor Auteursnamen ID
- 303779136
- Yale LUX ID
- person/5b5defba-1334-436a-9f2c-b7f6da9686e7
- ZbMATH author ID
- hoogendoorn.mark
🔗 Connections
Author of 20
A Comparative Study of State-of-the-Art Machine Learning Algorithms for Predictive Maintenance,
A Framework for Applying Natural Language Processing in Digital Health Interventions,
Attentive Group Equivariant Convolutional Networks,
Complex Machine-Learning Algorithms and Multivariable Logistic Regression on Par in the Prediction of Insufficient Clinical Response to Methotrexate in Rheumatoid Arthritis,
Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances,
End-to-end learning with interpretation on electrohysterography data to predict preterm birth,
Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support: Uniting Intensivists and Data Scientists,
Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing
+12 more
← Authored by 20
A Comparative Study of State-of-the-Art Machine Learning Algorithms for Predictive Maintenance,
A Framework for Applying Natural Language Processing in Digital Health Interventions,
Attentive Group Equivariant Convolutional Networks,
Complex Machine-Learning Algorithms and Multivariable Logistic Regression on Par in the Prediction of Insufficient Clinical Response to Methotrexate in Rheumatoid Arthritis,
Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances,
End-to-end learning with interpretation on electrohysterography data to predict preterm birth,
Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support: Uniting Intensivists and Data Scientists,
Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing
+12 more
Affiliated with 2
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Summary
Mark Hoogendoorn has worked as a researcher[1] and computer scientist[2].
FAQs
What did Mark Hoogendoorn do for work?
Mark Hoogendoorn worked as a researcher[1] and computer scientist[2].
Where did Mark Hoogendoorn go to school?
Mark Hoogendoorn was educated at Vrije Universiteit Amsterdam[3].