Johannes Brinkrolf

According to our database, Johannes Brinkrolf authored at least 22 papers between 2017 and 2023.

Collaborative distances:

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

2023

Model-based explanations of concept drift.

Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer

Neurocomputing, October, 2023

Combining self-labeling and demand based active learning for non-stationary data streams.

Valerie Vaquet, Fabian Hinder, Johannes Brinkrolf, Barbara Hammer

CoRR, 2023

On the Change of Decision Boundary and Loss in Learning with Concept Drift.

Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer

Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

On the Hardness and Necessity of Supervised Concept Drift Detection.

Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer

Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods, 2023

2022

On the Change of Decision Boundaries and Loss in Learning with Concept Drift.

Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer

CoRR, 2022

Localization of Concept Drift: Identifying the Drifting Datapoints.

Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, André Artelt, Barbara Hammer

Proceedings of the International Joint Conference on Neural Networks, 2022

Explaining Reject Options of Learning Vector Quantization Classifiers.

André Artelt, Johannes Brinkrolf, Roel Visser, Barbara Hammer

Proceedings of the 14th International Joint Conference on Computational Intelligence, 2022

Taking Care of Our Drinking Water: Dealing with Sensor Faults in Water Distribution Networks.

Valerie Vaquet, André Artelt, Johannes Brinkrolf, Barbara Hammer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Feature Selection for Trustworthy Regression Using Higher Moments.

Fabian Hinder, Johannes Brinkrolf, Barbara Hammer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Federated learning vector quantization for dealing with drift between nodes.

Johannes Brinkrolf, Valerie Vaquet, Fabian Hinder, Patrick Menz, Udo Seiffert, Barbara Hammer

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings.

Valerie Vaquet, Fabian Hinder, Jonas Vaquet, Johannes Brinkrolf, Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Fast Non-Parametric Conditional Density Estimation using Moment Trees.

Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

A Shape-Based Method for Concept Drift Detection and Signal Denoising.

Fabian Hinder, Johannes Brinkrolf, Valerie Vaquet, Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Evaluating Robustness of Counterfactual Explanations.

André Artelt, Valerie Vaquet, Riza Velioglu, Fabian Hinder, Johannes Brinkrolf, Malte Schilling, Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Federated Learning Vector Quantization.

Johannes Brinkrolf, Barbara Hammer

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020

Time integration and reject options for probabilistic output of pairwise LVQ.

Johannes Brinkrolf, Barbara Hammer

Neural Comput. Appl., 2020

Sparse Metric Learning in Prototype-based Classification.

Johannes Brinkrolf, Barbara Hammer

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Differential privacy for learning vector quantization.

Johannes Brinkrolf, Christina Göpfert, Barbara Hammer

Neurocomputing, 2019

2018

Interpretable machine learning with reject option.

Johannes Brinkrolf, Barbara Hammer

Autom., 2018

Differential private relevance learning.

Johannes Brinkrolf, Kolja Berger, Barbara Hammer

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017

Efficient kernelisation of discriminative dimensionality reduction.

Alexander Schulz, Johannes Brinkrolf, Barbara Hammer

Neurocomputing, 2017

Probabilistic extension and reject options for pairwise LVQ.

Johannes Brinkrolf, Barbara Hammer

Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017