Jesse H. Krijthe

According to our database, Jesse H. Krijthe authored at least 25 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Causal inference using observational intensive care unit data: a scoping review and recommendations for future practice.

J. M. Smit, Jesse H. Krijthe, W. M. R. Kant, J. A. Labrecque, M. Komorowski, D. A. M. P. J. Gommers, Jasper van Bommel, Marcel J. T. Reinders, Michel E. van Genderen

npj Digit. Medicine, 2023

Also for k-means: more data does not imply better performance.

Marco Loog, Jesse H. Krijthe, Manuele Bicego

Mach. Learn., 2023

When accurate prediction models yield harmful self-fulfilling prophecies.

Wouter A. C. van Amsterdam, Nan van Geloven, Jesse H. Krijthe, Rajesh Ranganath, Giovanni Ciná

CoRR, 2023

Detecting hidden confounding in observational data using multiple environments.

Rickard Karlsson, Jesse H. Krijthe

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Combining observational datasets from multiple environments to detect hidden confounding.

Rickard K. A. Karlsson, Jesse H. Krijthe

CoRR, 2022

Explaining Two Strange Learning Curves.

Zhiyi Chen, Marco Loog, Jesse H. Krijthe

Proceedings of the Artificial Intelligence and Machine Learning, 2022

2021

ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility.

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

Proceedings of the Reproducible Research in Pattern Recognition, 2021

2020

A Brief Prehistory of Double Descent.

Marco Loog, Tom J. Viering, Alexander Mey, Jesse H. Krijthe, David M. J. Tax

CoRR, 2020

2019

Nuclear discrepancy for single-shot batch active learning.

Tom J. Viering, Jesse H. Krijthe, Marco Loog

Mach. Learn., 2019

Robust Importance-Weighted Cross-Validation Under Sample Selection Bias.

Wouter M. Kouw, Jesse H. Krijthe, Marco Loog

Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

2018

The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning.

Jesse H. Krijthe, Marco Loog

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Robust semi-supervised least squares classification by implicit constraints.

Jesse H. Krijthe, Marco Loog

Pattern Recognit., 2017

Projected estimators for robust semi-supervised classification.

Jesse H. Krijthe, Marco Loog

Mach. Learn., 2017

Nuclear Discrepancy for Active Learning.

Tom J. Viering, Jesse H. Krijthe, Marco Loog

CoRR, 2017

On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL.

Marco Loog, Jesse H. Krijthe, Are Charles Jensen

CoRR, 2017

2016

Feature-Level Domain Adaptation.

Wouter M. Kouw, Laurens J. P. van der Maaten, Jesse H. Krijthe, Marco Loog

J. Mach. Learn. Res., 2016

The Pessimistic Limits of Margin-based Losses in Semi-supervised Learning.

Jesse H. Krijthe, Marco Loog

CoRR, 2016

The Peaking Phenomenon in Semi-supervised Learning.

Jesse H. Krijthe, Marco Loog

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2016

Optimistic semi-supervised least squares classification.

Jesse H. Krijthe, Marco Loog

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Reproducible Pattern Recognition Research: The Case of Optimistic SSL.

Jesse H. Krijthe, Marco Loog

Proceedings of the Reproducible Research in Pattern Recognition, 2016

RSSL: Semi-supervised Learning in R.

Jesse H. Krijthe

Proceedings of the Reproducible Research in Pattern Recognition, 2016

On Measuring and Quantifying Performance: error rates, surrogate Loss, and an Example in Semi-Supervised Learning.

Marco Loog, Jesse H. Krijthe, Are Charles Jensen

Proceedings of the Handbook of Pattern Recognition and Computer Vision, 5th Ed., 2016

2015

Implicitly Constrained Semi-supervised Least Squares Classification.

Jesse H. Krijthe, Marco Loog

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

2014

Implicitly Constrained Semi-supervised Linear Discriminant Analysis.

Jesse H. Krijthe, Marco Loog

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

2012

Improving cross-validation based classifier selection using meta-learning.

Jesse H. Krijthe, Tin Kam Ho, Marco Loog

Proceedings of the 21st International Conference on Pattern Recognition, 2012