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Tom Viering
Tom Viering
Verified email at tudelft.nl - Homepage
Title
Cited by
Cited by
Year
The shape of learning curves: a review
T Viering, M Loog
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7799-7819, 2022
1052022
A brief prehistory of double descent
M Loog, T Viering, A Mey, JH Krijthe, DMJ Tax
Proceedings of the National Academy of Sciences 117 (20), 10625-10626, 2020
692020
Minimizers of the empirical risk and risk monotonicity
M Loog, T Viering, A Mey
Advances in Neural Information Processing Systems 32, 2019
252019
Open problem: Monotonicity of learning
T Viering, A Mey, M Loog
Conference on Learning Theory, 3198-3201, 2019
222019
How to manipulate cnns to make them lie: the gradcam case
T Viering, Z Wang, M Loog, E Eisemann
arXiv preprint arXiv:1907.10901, 2019
202019
Is Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings
KG Schmahl, TJ Viering, S Makrodimitris, AN Jahfari, D Tax, M Loog
Proceedings of the Fourth Workshop on Natural Language Processing and …, 2020
152020
LCDB 1.0: An extensive learning curves database for classification tasks
F Mohr, TJ Viering, M Loog, JN van Rijn
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022
102022
Making learners (more) monotone
TJ Viering, A Mey, M Loog
International Symposium on Intelligent Data Analysis, 535-547, 2020
102020
Nuclear discrepancy for single-shot batch active learning
TJ Viering, JH Krijthe, M Loog
Machine Learning 108 (8), 1561-1599, 2019
72019
A survey of learning curves with bad behavior: or how more data need not lead to better performance
M Loog, T Viering
arXiv preprint arXiv:2211.14061, 2022
32022
On Safety in Machine Learning
TJ Viering
TU Delft, 2023
12023
A distribution dependent and independent complexity analysis of manifold regularization
A Mey, TJ Viering, M Loog
International Symposium on Intelligent Data Analysis, 326-338, 2020
12020
Nuclear discrepancy for active learning
TJ Viering, JH Krijthe, M Loog
arXiv preprint arXiv:1706.02645, 2017
12017
The Unreasonable Effectiveness Of Early Discarding After One Epoch In Neural Network Hyperparameter Optimization
R Egele, F Mohr, T Viering, P Balaprakash
arXiv preprint arXiv:2404.04111, 2024
2024
Different Approaches to Fitting and Extrapolating the Learning Curve
D Kim, T Viering
2022
To Tune or not to Tune: Hyperparameter Influence on the Learning Curve
P Bhaskaran, T Viering
2022
Active Learning by Discrepancy Minimization: A Comparison of Active Learning Methods Motivated by Generalization Bounds
TJ Viering
2016
Finding Non-Convex Classification Learning Curves by Estimating Convexity
K Gogora, T Viering
ON SAFETY IN MACHINE LEARNING
M JU, TOMJ VIERING
Generalization Bound Minimization for Active Learning
T Viering, J Krijthe, M Loog
Benelearn 2017: Proceedings of the Twenty-Sixth Benelux Conference on …, 0
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