Joaquin Vanschoren
Orcid: 0000-0001-7044-9805Affiliations:
- Eindhoven University of Technology, The Netherlands
According to our database1,
Joaquin Vanschoren
authored at least 110 papers
between 2007 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on tue.nl
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on orcid.org
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on github.com
On csauthors.net:
Bibliography
2024
J. Artif. Intell. Res., 2024
FOCIL: Finetune-and-Freeze for Online Class Incremental Learning by Training Randomly Pruned Sparse Experts.
CoRR, 2024
CoRR, 2024
2023
Mach. Learn., June, 2023
Signal Quality Analysis for Long-Term ECG Monitoring Using a Health Patch in Cardiac Patients.
Sensors, February, 2023
Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates.
CoRR, 2023
An Analysis of Evolutionary Migration Models for Multi-Objective, Multi-Fidelity Automl.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the 34th British Machine Vision Conference 2023, 2023
Proceedings of the International Conference on Automated Machine Learning, 2023
2022
Theory-based habit modeling for enhancing behavior prediction in behavior change support systems.
User Model. User Adapt. Interact., 2022
Introduction to the Special Section on AI in Manufacturing: Current Trends and Challenges.
SIGKDD Explor., 2022
CoRR, 2022
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Multi-fidelity optimization method with asynchronous generalized island model for AutoML.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the ECML/PKDD Workshop on Meta-Knowledge Transfer, 2022
2021
Proc. VLDB Endow., 2021
IEEE Trans. Pattern Anal. Mach. Intell., 2021
CoRR, 2021
Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classification.
CoRR, 2021
Fixed-point Quantization of Convolutional Neural Networks for Quantized Inference on Embedded Platforms.
CoRR, 2021
CoRR, 2021
Proceedings of the NeurIPS 2022 Competition Track, 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021
2020
Mach. Learn., 2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020
2019
Multi-task learning with a natural metric for quantitative structure activity relationship learning.
J. Cheminformatics, 2019
A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers.
Inf. Sci., 2019
Comput. Stat., 2019
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019
2018
The online performance estimation framework: heterogeneous ensemble learning for data streams.
Mach. Learn., 2018
Mach. Learn., 2018
Speeding up algorithm selection using average ranking and active testing by introducing runtime.
Mach. Learn., 2018
CoRR, 2018
Data Augmentation using Conditional Generative Adversarial Networks for Leaf Counting in Arabidopsis Plants.
Proceedings of the British Machine Vision Conference 2018, 2018
2017
CoRR, 2017
Proceedings of the International Workshop on Automatic Selection, 2017
2016
Toward understanding online sentiment expression: an interdisciplinary approach with subgroup comparison and visualization.
Soc. Netw. Anal. Min., 2016
Proceedings of the Advances in Ontology Design and Patterns [revised and extended versions of the papers presented at the 7th edition of the Workshop on Ontology and Semantic Web Patterns, 2016
Anticipating habit formation: a psychological computing approach to behavior change support.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2016 ACM International Symposium on Wearable Computers, 2016
Proceedings of the 5th Brazilian Conference on Intelligent Systems, 2016
2015
Towards a Collaborative Platform for Advanced Meta-Learning in Healthcare Predictive Analytics.
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015
Meta-learning Recommendation of Default Hyper-parameter Values for SVMs in Classification Tasks.
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015
Proceedings of the 4th International Workshop on Big Data, 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
To tune or not to tune: Recommending when to adjust SVM hyper-parameters via meta-learning.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015
Decreasing the False Alarm Rate of Arrhythmias in Intensive Care Using a Machine Learning Approach.
Proceedings of the Computing in Cardiology, 2015
Who is More Positive in Private? Analyzing Sentiment Differences across Privacy Levels and Demographic Factors in Facebook Chats and Posts.
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2015
2014
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014
Proceedings of the Discovery Science - 17th International Conference, 2014
2013
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013
2012
Mach. Learn., 2012
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2012
2011
Proceedings of the Meta-Learning in Computational Intelligence, 2011
Proceedings of the Advances in Intelligent Data Analysis X - 10th International Symposium, 2011
Proceedings of the Handbuch Forschungsdatenmanagement., 2011
2010
Understanding Machine Learning Performance with Experiment Databases (Het verwerven van inzichten in leerperformantie met experiment databanken) ; Understanding Machine Learning Performance with Experiment Databases.
PhD thesis, 2010
Proceedings of the Inductive Databases and Constraint-Based Data Mining., 2010
2009
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009
2008
Proceedings of the PRICAI 2008: Trends in Artificial Intelligence, 2008
Proceedings of the Leveraging Applications of Formal Methods, 2008
2007
Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007
Proceedings of the Data Analysis, Machine Learning and Applications, 2007