Jesse H. Krijthe
Jesse H. Krijthe
Radboud University Nijmegen
Verified email at tudelft.nl - Homepage
TitleCited byYear
Rtsne: T-distributed stochastic neighbor embedding using Barnes-Hut implementation
JH Krijthe
R package version 0.13, URL https://github. com/jkrijthe/Rtsne, 2015
112*2015
Implicitly constrained semi-supervised least squares classification
JH Krijthe, M Loog
International symposium on intelligent data analysis, 158-169, 2015
212015
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
202016
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, 24949, 2016
142016
Implicitly Constrained Semi-Supervised Linear Discriminant Analysis
JH Krijthe, M Loog
Pattern Recognition (ICPR), 2014 22nd International Conference on, 3762-3767, 2014
132014
Syntactic pattern recognition: paradigm issues and open problems
M Flasiński
Handbook of Pattern Recognition and Computer Vision, 3-25, 2016
122016
Robust semi-supervised least squares classification by implicit constraints
JH Krijthe, M Loog
Pattern Recognition 63, 115-126, 2017
112017
Projected estimators for robust semi-supervised classification
JH Krijthe, M Loog
Machine Learning 106 (7), 993-1008, 2017
92017
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
82016
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
82012
Optimistic semi-supervised least squares classification
JH Krijthe, M Loog
2016 23rd International Conference on Pattern Recognition (ICPR), 1677-1682, 2016
62016
RSSL: Semi-supervised Learning in R
JH Krijthe
International Workshop on Reproducible Research in Pattern Recognition, 104-115, 2016
52016
Rtsne: t-distributed stochastic neighbor embedding using Barnes-Hut implementation https://github. com/jkrijthe
J Krijthe
Rtsne, 2015
52015
The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning
JH Krijthe, M Loog
arXiv preprint arXiv:1612.08875, 2016
22016
The pessimistic limits and possibilities of margin-based losses in semi-supervised learning
J Krijthe, M Loog
Advances in Neural Information Processing Systems, 1790-1799, 2018
12018
Reproducible Pattern Recognition Research: The Case of Optimistic SSL
JH Krijthe, M Loog
International Workshop on Reproducible Research in Pattern Recognition, 48-59, 2016
12016
The peaking phenomenon in semi-supervised learning
JH Krijthe, M Loog
Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2016
12016
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, 2019
2019
Predicting Pelvic Floor Surgery Outcomes
T Welten, T Heskes, J Krijthe
2019
Sex-Specific Patient Journeys in Early Parkinson's Disease in the Netherlands
FP Vlaanderen, Y de Man, JH Krijthe, MAC Tanke, AS Groenewoud, ...
Frontiers in Neurology 10, 2019
2019
The system can't perform the operation now. Try again later.
Articles 1–20