Mark Hoogendoorn

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 90

Top Venues

CoRR

SSCI

Comput. Biol. Medicine

Publications

Floris den Hengst, Martijn Otten, Paul W. G. Elbers, Frank van Harmelen, Vincent François-Lavet, Mark Hoogendoorn
Guideline-informed reinforcement learning for mechanical ventilation in critical care. Artif. Intell. Medicine 147 (2024)
Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
Latent Assistance Networks: Rediscovering Hyperbolic Tangents in RL. CoRR (2024)
David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series. Trans. Mach. Learn. Res. 2024 (2024)
Frank C. Bennis, Claire Aussems, Joke C. Korevaar, Mark Hoogendoorn
The added value of temporal data and the best way to handle it: A use-case for atrial fibrillation using general practitioner data. Comput. Biol. Medicine 171 (2024)
Arwin Gansekoele, Alexios Balatsoukas-Stimming, Tom Brusse, Mark Hoogendoorn, Sandjai Bhulai, Rob van der Mei
A Machine Learning Approach for Simultaneous Demapping of QAM and APSK Constellations. CoRR (2024)
Arwin Gansekoele, Tycho Bot, Rob van der Mei, Sandjai Bhulai, Mark Hoogendoorn
Unveiling the Potential: Harnessing Deep Metric Learning to Circumvent Video Streaming Encryption. CoRR (2024)
Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. ECAI (2023)
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal
Channel-Adaptive Early Exiting Using Reinforcement Learning for Multivariate Time Series Classification. ICMLA (2023)
Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. CoRR (2023)
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal
Multivariate Time Series Early Classification Across Channel and Time Dimensions. CoRR (2023)
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal
Reinforcement Learning-Guided Channel Selection Across Time for Multivariate Time Series Classification. SSCI (2023)
Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
Disentangled (Un)Controllable Features. SSCI (2023)
Arwin Gansekoele, Tycho Bot, Rob van der Mei, Sandjai Bhulai, Mark Hoogendoorn
Unveiling the Potential: Harnessing Deep Metric Learning to Circumvent Video Streaming Encryption. WI/IAT (2023)
Tariq A. Dam, Lucas M. Fleuren, Luca F. Roggeveen, Martijn Otten, Laurens Biesheuvel, Ameet R. Jagesar, Robbert C. A. Lalisang, Robert F. J. Kullberg, Tom Hendriks, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul W. G. Elbers
Augmented intelligence facilitates concept mapping across different electronic health records. Int. J. Medical Informatics 179 (2023)
Anne M. Fischer, Alex Rietveld, Peter Teunissen, P. C. A. M. Bakker, Mark Hoogendoorn
End-to-end learning with interpretation on electrohysterography data to predict preterm birth. Comput. Biol. Medicine 158 (2023)
Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
Improving Generalization in Reinforcement Learning Through Forked Agents. IEA/AIE (2) (2023)
David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke
Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN. ICLR (2023)
David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke
Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN. CoRR (2023)
Etienne van de Bijl, Jan Klein, Joris Pries, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei
The Dutch Draw: Constructing a Universal Baseline for Binary Prediction Models. CoRR (2022)
Olivier Moulin, Francois Vincent-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. WI/IAT (2022)
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal
Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS. CoRR (2022)
David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn
CKConv: Continuous Kernel Convolution For Sequential Data. ICLR (2022)
David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert
FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes. ICLR (2022)
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal
An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions. ICMLA (2022)
Eoin Martino Grua, Martina De Sanctis, Ivano Malavolta, Mark Hoogendoorn, Patricia Lago
An evaluation of the effectiveness of personalization and self-adaptation for e-Health apps. Inf. Softw. Technol. 146 (2022)
David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn
Towards a General Purpose CNN for Long Range Dependencies in ND. CoRR (2022)
Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen
Reinforcement Learning with Option Machines. IJCAI (2022)
Luis Pedro Silvestrin, Harry van Zanten, Mark Hoogendoorn, Ger Koole
Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Case. CoRR (2022)
Olivier Moulin, Vincent François-Lavet, Mark Hoogendoorn
Improving generalization in reinforcement learning through forked agents. CoRR (2022)
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri Bal
An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions. CoRR (2022)
Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
Disentangled (Un)Controllable Features. CoRR (2022)
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal
Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS. DCOSS (2022)
Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen
Planning for potential: efficient safe reinforcement learning. Mach. Learn. 111 (6) (2022)
Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
Improving adaptability to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. CoRR (2022)
Daniel Lutscher, Ali el Hassouni, Maarten Stol, Mark Hoogendoorn
Mixing Consistent Deep Clustering. LOD (2021)
David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
CKConv: Continuous Kernel Convolution For Sequential Data. CoRR (2021)
Luis P. Silvestrin, Leonardos Pantiskas, Mark Hoogendoorn
A Framework for Imbalanced Time-Series Forecasting. LOD (2021)
David W. Romero, Robert-Jan Bruintjes, Jakub M. Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan C. van Gemert
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes. CoRR (2021)
Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Robert D. van der Mei
Plusmine: Dynamic Active Learning with Semi-Supervised Learning for Automatic Classification. WI/IAT (2021)
Luis P. Silvestrin, Leonardos Pantiskas, Mark Hoogendoorn
A Framework for Imbalanced Time-series Forecasting. CoRR (2021)
Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei
Jasmine: A New Active Learning Approach to Combat Cybercrime. CoRR (2021)
Jie Jiang, Qiuqiang Kong, Mark D. Plumbley, Nigel Gilbert, Mark Hoogendoorn, Diederik M. Roijers
Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances. ACM Trans. Knowl. Discov. Data 15 (3) (2021)
Luca Roggeveen, Ali el Hassouni, Jonas Ahrendt, Tingjie Guo, Lucas Fleuren, Patrick Thoral, Armand R. J. Girbes, Mark Hoogendoorn, Paul W. G. Elbers
Transatlantic transferability of a new reinforcement learning model for optimizing haemodynamic treatment for critically ill patients with sepsis. Artif. Intell. Medicine 112 (2021)
Ali el Hassouni, Mark Hoogendoorn, Marketa Ciharova, Annet Kleiboer, Khadicha Amarti, Vesa Muhonen, Heleen Riper, A. E. Eiben
pH-RL: A Personalization Architecture to Bring Reinforcement Learning to Health Practice. LOD (2021)
Ali el Hassouni, Mark Hoogendoorn, Marketa Ciharova, Annet Kleiboer, Khadicha Amarti, Vesa Muhonen, Heleen Riper, A. E. Eiben
pH-RL: A personalization architecture to bring reinforcement learning to health practice. CoRR (2021)
David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Attentive Group Equivariant Convolutional Networks. ICML (2020)
David W. Romero, Mark Hoogendoorn
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data. ICLR (2020)
Olga Pólchlopek, Nynke R. Koning, Frederike L. Büchner, Mathilde R. Crone, Mattijs E. Numans, Mark Hoogendoorn
Quantitative and temporal approach to utilising electronic medical records from general practices in mental health prediction. Comput. Biol. Medicine 125 (2020)
Xixi Lu, Seyed Amin Tabatabaei, Mark Hoogendoorn, Hajo A. Reijers
Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns. CoRR (2020)
Floris den Hengst, Eoin Martino Grua, Ali el Hassouni, Mark Hoogendoorn
Reinforcement learning for personalization: A systematic literature review. Data Sci. 3 (2) (2020)
Daniel Lutscher, Ali el Hassouni, Maarten Stol, Mark Hoogendoorn
Mixing Consistent Deep Clustering. CoRR (2020)
Ali el Hassouni, Mark Hoogendoorn, A. E. Eiben, Vesa Muhonen
Structural and Functional Representativity of GANs for Data Generation in Sequential Decision Making. LOD (1) (2020)
David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms. CoRR (2020)
Seyed Amin Tabatabaei, Jan Klein, Mark Hoogendoorn
Score for Learning from Positive and Unlabeled Examples. LOD (1) (2020)
David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Attentive Group Equivariant Convolutional Networks. CoRR (2020)
Eoin Martino Grua, Mark Hoogendoorn, Ivano Malavolta, Patricia Lago, A. E. Eiben
CluStream-GT: Online Clustering for Personalization in the Health Domain. WI (2019)
Caleb Mensah, Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei
Detecting Fraudulent Bookings of Online Travel Agencies with Unsupervised Machine Learning. IEA/AIE (2019)
Seyed Amin Tabatabaei, Xixi Lu, Mark Hoogendoorn, Hajo A. Reijers
Identifying Patient Groups based on Frequent Patterns of Patient Samples. CoRR (2019)
Floris den Hengst, Mark Hoogendoorn, Frank van Harmelen, Joost Bosman
Reinforcement Learning for Personalized Dialogue Management. WI (2019)
David W. Romero, Mark Hoogendoorn
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data. CoRR (2019)
Mark Hoogendoorn, Ward van Breda, Jeroen Ruwaard
GP-HD: Using Genetic Programming to Generate Dynamical Systems Models for Health Care. CoRR (2019)
Alessandro Zonta, Selmar K. Smit, Mark Hoogendoorn, A. E. Eiben
Generation of Human-Like Movements Based on Environmental Features. SSCI (2019)
Floris den Hengst, Mark Hoogendoorn, Frank van Harmelen, Joost Bosman
Reinforcement Learning for Personalized Dialogue Management. CoRR (2019)
Mark Hoogendoorn, Ward van Breda, Jeroen Ruwaard
GP-HD: Using Genetic Programming to Generate Dynamical Systems Models for Health Care. WI (2019)
Xixi Lu, Seyed Amin Tabatabaei, Mark Hoogendoorn, Hajo A. Reijers
Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns. BPM (2019)
Ali el Hassouni, Mark Hoogendoorn, A. E. Eiben, Martijn van Otterlo, Vesa Muhonen
End-to-end Personalization of Digital Health Interventions using Raw Sensor Data with Deep Reinforcement Learning. WI (2019)
Luis P. Silvestrin, Mark Hoogendoorn, Ger Koole
A Comparative Study of State-of-the-Art Machine Learning Algorithms for Predictive Maintenance. SSCI (2019)
Seyed Amin Tabatabaei, Xixi Lu, Mark Hoogendoorn, Hajo A. Reijers
Identifying Patient Groups based on Frequent Patterns of Patient Samples. HealthCom (2019)
Eoin Martino Grua, Mark Hoogendoorn
Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing. SSCI (2018)
Ali el Hassouni, Mark Hoogendoorn, Martijn van Otterlo, Eduardo Barbaro
Personalization of Health Interventions using Cluster-Based Reinforcement Learning. CoRR (2018)
Ali el Hassouni, Mark Hoogendoorn, Vesa Muhonen
Using Generative Adversarial Networks to Develop a Realistic Human Behavior Simulator. PRIMA (2018)
Jan Klein, Sandjai Bhulai, Mark Hoogendoorn, Rob van der Mei, Raymond Hinfelaar
Detecting Network Intrusion beyond 1999: Applying Machine Learning Techniques to a Partially Labeled Cybersecurity Dataset. WI (2018)
Seyed Amin Tabatabaei, Mark Hoogendoorn, Aart van Halteren
Narrowing Reinforcement Learning: Overcoming the Cold Start Problem for Personalized Health Interventions. PRIMA (2018)
Ali el Hassouni, Mark Hoogendoorn, Martijn van Otterlo, Eduardo Barbaro
Personalization of Health Interventions Using Cluster-Based Reinforcement Learning. PRIMA (2018)
Jie Jiang, Mark Hoogendoorn, Qiuqiang Kong, Diederik M. Roijers, Nigel Gilbert
Predicting Appliance Usage Status In Home Like Environments. DSL (2018)
Ryan Amirkhan, Mark Hoogendoorn, Mattijs E. Numans, Leon M. G. Moons
Using recurrent neural networks to predict colorectal cancer among patients. SSCI (2017)
Ward van Breda, Mark Hoogendoorn, A. E. Eiben, Matthias Berking
Assessment of temporal predictive models for health care using a formal method. Comput. Biol. Medicine 87 (2017)
Mark Hoogendoorn, Thomas Berger, Ava Schulz, Timo Stolz, Peter Szolovits
Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations. IEEE J. Biomed. Health Informatics 21 (5) (2017)
Mark Hoogendoorn, Peter Szolovits, Leon M. G. Moons, Mattijs E. Numans
Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer. Artif. Intell. Medicine 69 (2016)
Mark Hoogendoorn, Ali el Hassouni, Kwongyen Mok, Marzyeh Ghassemi, Peter Szolovits
Prediction using patient comparison vs. modeling: A case study for mortality prediction. EMBC (2016)
Reinier Kop, Mark Hoogendoorn, Annette ten Teije, Frederike L. Büchner, Pauline Slottje, Leon M. G. Moons, Mattijs E. Numans
Predictive modeling of colorectal cancer using a dedicated pre-processing pipeline on routine electronic medical records. Comput. Biol. Medicine 76 (2016)
Ward R. J. van Breda, Mark Hoogendoorn, A. E. Eiben, Gerhard Andersson, Heleen Riper, Jeroen Ruwaard, Kristofer Vernmark
A feature representation learning method for temporal datasets. SSCI (2016)
Giorgos Karafotias, Mark Hoogendoorn, A. E. Eiben
Evaluating Reward Definitions for Parameter Control. EvoApplications (2015)
Shu Gao, Mark Hoogendoorn
Using Evolutionary Algorithms to Personalize Controllers in Ambient Intelligence. ISAmI (2015)
Giorgos Karafotias, Mark Hoogendoorn, Ágoston E. Eiben
Parameter Control in Evolutionary Algorithms: Trends and Challenges. IEEE Trans. Evol. Comput. 19 (2) (2015)
Reinier Kop, Armon Toubman, Mark Hoogendoorn, Jan Joris Roessingh
Evolutionary Dynamic Scripting: Adaptation of Expert Rule Bases for Serious Games. IEA/AIE (2015)
Reinier Kop, Mark Hoogendoorn, Leon M. G. Moons, Mattijs E. Numans, Annette ten Teije
On the Advantage of Using Dedicated Data Mining Techniques to Predict Colorectal Cancer. AIME (2015)
Tibor Bosse, Mark Hoogendoorn
Special issue on advances in applied artificial intelligence. Appl. Intell. 42 (1) (2015)
Ward R. J. van Breda, Mark Hoogendoorn, A. E. Eiben, Matthias Berking
An Evaluation Framework for the Comparison of Fine-Grained Predictive Models in Health Care. AIME (2015)
Richard Koopmanschap, Mark Hoogendoorn, Jan Joris Roessingh
Tailoring a cognitive model for situation awareness using machine learning. Appl. Intell. 42 (1) (2015)
Reinier Kop, Mark Hoogendoorn, Michel C. A. Klein
A Personalized Support Agent for Depressed Patients: Forecasting Patient Behavior Using a Mood and Coping Model. WI-IAT (3) (2014)
Giorgos Karafotias, Mark Hoogendoorn, Berend Weel
Comparing generic parameter controllers for EAs. FOCI (2014)
Xander Wilcke, Mark Hoogendoorn, Jan Joris Roessingh
Co-evolutionary Learning for Cognitive Computer Generated Entities. IEA/AIE (2) (2014)
Mark Hoogendoorn, Syed Waqar Jaffry, Peter-Paul van Maanen, Jan Treur
Design and validation of a relative trust model. Knowl. Based Syst. 57 (2014)
Diti Oudendag, Mark Hoogendoorn, Roel Jongeneel
Agent-Based Modeling of Farming Behavior: A Case Study for Milk Quota Abolishment. IEA/AIE (1) (2014)
Giorgos Karafotias, Ágoston E. Eiben, Mark Hoogendoorn
Generic parameter control with reinforcement learning. GECCO (2014)
Mark Hoogendoorn, Leon M. G. Moons, Mattijs E. Numans, Robert-Jan Sips
Utilizing Data Mining for Predictive Modeling of Colorectal Cancer Using Electronic Medical Records. Brain Informatics and Health (2014)
Pietro Cipresso, Mark Hoogendoorn, Michel C. A. Klein, Aleksandar Matic
Special Issue "Technology for Mental Health". EAI Endorsed Trans. Ambient Syst. 1 (2) (2013)
Giorgos Karafotias, Mark Hoogendoorn, A. E. Eiben
Parameter control: strategy or luck? GECCO (Companion) (2013)
Tibor Bosse, Fiemke Both, Rob Duell, Mark Hoogendoorn, Michel C. A. Klein, Rianne van Lambalgen, Andy van der Mee, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos
An ambient agent system assisting humans in complex tasks by analysis of a human's state and performance. Int. J. Intell. Inf. Database Syst. 7 (1) (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mark Hoogendoorn