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Jesse H. Krijthe
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Rtsne: T-distributed stochastic neighbor embedding using Barnes-Hut implementation
JH Krijthe
R package version 0.13, URL https://github. com/jkrijthe/Rtsne, 2015
377*2015
Feature-level domain adaptation
WM Kouw, LJP Van Der Maaten, JH Krijthe, M Loog
The Journal of Machine Learning Research 17 (1), 5943-5974, 2016
582016
Measuring Parkinson's disease over time: the real‐world within‐subject reliability of the MDS‐UPDRS
LJW Evers, JH Krijthe, MJ Meinders, BR Bloem, TM Heskes
Movement Disorders 34 (10), 1480-1487, 2019
562019
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
312020
Pan-cancer subtyping in a 2D-map shows substructures that are driven by specific combinations of molecular characteristics
E Taskesen, SMH Huisman, A Mahfouz, JH Krijthe, J De Ridder, ...
Scientific reports 6 (1), 1-14, 2016
302016
Implicitly constrained semi-supervised least squares classification
JH Krijthe, M Loog
International symposium on intelligent data analysis, 158-169, 2015
242015
Real-life gait performance as a digital biomarker for motor fluctuations: The Parkinson@ Home validation study
LJW Evers, YP Raykov, JH Krijthe, ALS De Lima, R Badawy, K Claes, ...
Journal of medical Internet research 22 (10), e19068, 2020
222020
Implicitly Constrained Semi-Supervised Linear Discriminant Analysis
JH Krijthe, M Loog
Pattern Recognition (ICPR), 2014 22nd International Conference on, 3762-3767, 2014
182014
Projected estimators for robust semi-supervised classification
JH Krijthe, M Loog
Machine Learning 106 (7), 993-1008, 2017
162017
RSSL: Semi-supervised Learning in R
JH Krijthe
International Workshop on Reproducible Research in Pattern Recognition, 104-115, 2016
152016
Robust semi-supervised least squares classification by implicit constraints
JH Krijthe, M Loog
Pattern Recognition 63, 115-126, 2017
142017
On measuring and quantifying performance: error rates, surrogate loss, and an example in semi-supervised learning
M Loog, JH Krijthe, AC Jensen
Handbook of Pattern Recognition and Computer Vision, 53-68, 2016
112016
Improving cross-validation based classifier selection using meta-learning
JH Krijthe, TK Ho, M Loog
Proceedings of the 21st International Conference on Pattern Recognition …, 2012
92012
Autoencoding Credit Card Fraud
T Sweers, T Heskes, J Krijthe
Bachelor Thesis, 2018
62018
Optimistic semi-supervised least squares classification
JH Krijthe, M Loog
2016 23rd International Conference on Pattern Recognition (ICPR), 1677-1682, 2016
62016
Possible modification of BRSK1 on the risk of alkylating chemotherapy-related reduced ovarian function
ALLF Van der Kooi, M Van Dijk, L Broer, MH Van Den Berg, JSE Laven, ...
Human Reproduction 36 (4), 1120-1133, 2021
52021
ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility
B Yildiz, H Hung, JH Krijthe, C Liem, M Loog, G Migut, FA Oliehoek, ...
International Workshop on Reproducible Research in Pattern Recognition, 3-11, 2021
52021
Estimating the effect of early treatment initiation in Parkinson's disease using observational data
L van den Heuvel, LJW Evers, MJ Meinders, B Post, AM Stiggelbout, ...
Movement Disorders 36 (2), 407-414, 2021
42021
The pessimistic limits and possibilities of margin-based losses in semi-supervised learning
J Krijthe, M Loog
Advances in Neural Information Processing Systems 31, 2018
42018
The pessimistic limits of margin-based losses in semi-supervised learning
JH Krijthe, M Loog
arXiv preprint arXiv:1612.08875, 2016
42016
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Articles 1–20