Jesse H. Krijthe

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 27

Top Topics

Sample Selection

Supervised Classification

Observational Data

Supervised Learning

Top Venues

Publications

J. M. Smit, Jesse H. Krijthe, W. M. R. Kant, J. A. Labrecque, M. Komorowski, D. A. M. P. J. Gommers, J. van Bommel, Marcel J. T. Reinders, M. E. van Genderen
Causal inference using observational intensive care unit data: a scoping review and recommendations for future practice. npj Digit. Medicine 6 (2023)
Rickard Karlsson, Jesse H. Krijthe
Detecting hidden confounding in observational data using multiple environments. NeurIPS (2023)
Wouter A. C. van Amsterdam, Nan van Geloven, Jesse H. Krijthe, Rajesh Ranganath, Giovanni Ciná
When accurate prediction models yield harmful self-fulfilling prophecies. CoRR (2023)
Marco Loog, Jesse H. Krijthe, Manuele Bicego
Also for k-means: more data does not imply better performance. Mach. Learn. 112 (8) (2023)
Zhiyi Chen, Marco Loog, Jesse H. Krijthe
Explaining Two Strange Learning Curves. BNAIC/BENELEARN (2022)
Rickard K. A. Karlsson, Jesse H. Krijthe
Combining observational datasets from multiple environments to detect hidden confounding. CoRR (2022)
Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C. S. Liem, Marco Loog, Gosia Migut, Frans A. Oliehoek, Annibale Panichella, Przemyslaw Pawelczak, Stjepan Picek, Mathijs de Weerdt, Jan van Gemert
ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility. RRPR (2021)
Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C. S. Liem, Marco Loog, Gosia Migut, Frans A. Oliehoek, Annibale Panichella, Przemyslaw Pawelczak, Stjepan Picek, Mathijs de Weerdt, Jan van Gemert
ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility. CoRR (2020)
Marco Loog, Tom J. Viering, Alexander Mey, Jesse H. Krijthe, David M. J. Tax
A Brief Prehistory of Double Descent. CoRR (2020)
Wouter M. Kouw, Jesse H. Krijthe, Marco Loog
Robust Importance-Weighted Cross-Validation Under Sample Selection Bias. MLSP (2019)
Tom J. Viering, Jesse H. Krijthe, Marco Loog
Nuclear discrepancy for single-shot batch active learning. Mach. Learn. 108 (8-9) (2019)
Jesse H. Krijthe, Marco Loog
The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning. NeurIPS (2018)
Jesse H. Krijthe, Marco Loog
Robust semi-supervised least squares classification by implicit constraints. Pattern Recognit. 63 (2017)
Marco Loog, Jesse H. Krijthe, Are Charles Jensen
On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL. CoRR (2017)
Jesse H. Krijthe, Marco Loog
Projected estimators for robust semi-supervised classification. Mach. Learn. 106 (7) (2017)
Tom J. Viering, Jesse H. Krijthe, Marco Loog
Nuclear Discrepancy for Active Learning. CoRR (2017)
Jesse H. Krijthe, Marco Loog
Optimistic semi-supervised least squares classification. ICPR (2016)
Jesse H. Krijthe, Marco Loog
The Pessimistic Limits of Margin-based Losses in Semi-supervised Learning. CoRR (2016)
Wouter M. Kouw, Laurens J. P. van der Maaten, Jesse H. Krijthe, Marco Loog
Feature-Level Domain Adaptation. J. Mach. Learn. Res. 17 (2016)
Jesse H. Krijthe, Marco Loog
The Peaking Phenomenon in Semi-supervised Learning. CoRR (2016)
Jesse H. Krijthe, Marco Loog
Reproducible Pattern Recognition Research: The Case of Optimistic SSL. CoRR (2016)
Jesse H. Krijthe, Marco Loog
Reproducible Pattern Recognition Research: The Case of Optimistic SSL. RRPR@ICPR (2016)
Jesse H. Krijthe
RSSL: Semi-supervised Learning in R. RRPR@ICPR (2016)
Jesse H. Krijthe, Marco Loog
Optimistic Semi-supervised Least Squares Classification. CoRR (2016)
Jesse H. Krijthe, Marco Loog
The Peaking Phenomenon in Semi-supervised Learning. S+SSPR (2016)
Jesse H. Krijthe, Marco Loog
Projected Estimators for Robust Semi-supervised Classification. CoRR (2016)
Jesse H. Krijthe
RSSL: Semi-supervised Learning in R. CoRR (2016)
Jesse H. Krijthe, Marco Loog
Implicitly Constrained Semi-Supervised Least Squares Classification. CoRR (2015)
Jesse H. Krijthe, Marco Loog
Implicitly Constrained Semi-supervised Least Squares Classification. IDA (2015)
Wouter M. Kouw, Jesse H. Krijthe, Marco Loog, Laurens J. P. van der Maaten
Feature-Level Domain Adaptation. CoRR (2015)
Jesse H. Krijthe, Marco Loog
Robust Semi-supervised Least Squares Classification by Implicit Constraints. CoRR (2015)
Jesse H. Krijthe, Marco Loog
Implicitly Constrained Semi-supervised Linear Discriminant Analysis. ICPR (2014)
Jesse H. Krijthe, Marco Loog
Implicitly Constrained Semi-Supervised Linear Discriminant Analysis. CoRR (2014)
Jesse H. Krijthe, Tin Kam Ho, Marco Loog
Improving cross-validation based classifier selection using meta-learning. ICPR (2012)