Alexander Schulz

According to our database, Alexander Schulz authored at least 41 papers between 2012 and 2024.

Collaborative distances:

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

2024

Targeted Visualization of the Backbone of Encoder LLMs.

Isaac Roberts, Alexander Schulz, Luca Hermes, Barbara Hammer

CoRR, 2024

Semantic Properties of Cosine Based Bias Scores for Word Embeddings.

Sarah Schröder, Alexander Schulz, Fabian Hinder, Barbara Hammer

Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods, 2024

Predicting the Level of Co-Activation of One Muscle Head from the Other Muscle Head of the Biceps Brachii Muscle by Linear Regression and Shallow Feedforward Neural Networks.

Nils Grimmelsmann, Malte Mechtenberg, Markus Vieth, Alexander Schulz, Barbara Hammer, Axel Schneider

Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies, 2024

2023

Metric Learning with Self-Adjusting Memory for Explaining Feature Drift.

Johannes Kummert, Alexander Schulz, Barbara Hammer

SN Comput. Sci., July, 2023

Generating Cardiovascular Data to Improve Training of Assistive Heart Devices.

Johannes Kummert, Alexander Schulz, Robert Feldhans, Moriz Habigt, Maike Stemmler, Christina Kohler, Dirk Abel, Rolf Rossaint, Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Data Augmentation for Cardiovascular Time Series Data Using WaveNet.

Robert Feldhans, Alexander Schulz, Johannes Kummert, Moriz Habigt, Maike Stemmler, Christina Kohler, Dirk Abel, Rolf Rossaint, Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Extending Drift Detection Methods to Identify When Exactly the Change Happened.

Markus Vieth, Alexander Schulz, Barbara Hammer

Proceedings of the Advances in Computational Intelligence, 2023

Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation.

Sarah Schröder, Alexander Schulz, Ivan Tarakanov, Robert Feldhans, Barbara Hammer

Proceedings of the Advances in Computational Intelligence, 2023

So Can We Use Intrinsic Bias Measures or Not?

Sarah Schröder, Alexander Schulz, Philip Kenneweg, Barbara Hammer

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

Debiasing Sentence Embedders Through Contrastive Word Pairs.

Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer

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

"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction.

André Artelt, Alexander Schulz, Barbara Hammer

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

2022

Reservoir Memory Machines as Neural Computers.

Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer

IEEE Trans. Neural Networks Learn. Syst., 2022

Reservoir stack machines.

Benjamin Paaßen, Alexander Schulz, Barbara Hammer

Neurocomputing, 2022

The SAME score: Improved cosine based bias score for word embeddings.

Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer

CoRR, 2022

BERT WEAVER: Using WEight AVERaging to Enable Lifelong Learning for Transformer-based Models.

Lisa Langnickel, Alexander Schulz, Barbara Hammer, Juliane Fluck

CoRR, 2022

Intelligent Learning Rate Distribution to Reduce Catastrophic Forgetting in Transformers.

Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2022, 2022

2021

Efficient Reject Options for Particle Filter Object Tracking in Medical Applications.

Johannes Kummert, Alexander Schulz, Tim Redick, Nassim Ayoub, Ali Modabber, Dirk Abel, Barbara Hammer

Sensors, 2021

Evaluating Metrics for Bias in Word Embeddings.

Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer

CoRR, 2021

2020

DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction.

Alexander Schulz, Fabian Hinder, Barbara Hammer

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Reservoir memory machines.

Benjamin Paassen, Alexander Schulz

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

2019

DeepView: Visualizing the behavior of deep neural networks in a part of the data space.

Alexander Schulz, Fabian Hinder, Barbara Hammer

CoRR, 2019

2018

Expectation maximization transfer learning and its application for bionic hand prostheses.

Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer

Neurocomputing, 2018

Transfer Learning of Complex Motor Skills on the Humanoid Robot Affetto.

Alexander Schulz, Jeffrey Frederic Queißer, Hisashi Ishihara, Minoru Asada

Proceedings of the 2018 Joint IEEE 8th International Conference on Development and Learning and Epigenetic Robotics, 2018

2017

Efficient kernelisation of discriminative dimensionality reduction.

Alexander Schulz, Johannes Brinkrolf, Barbara Hammer

Neurocomputing, 2017

Linear supervised transfer learning for the large margin nearest neighbor classifier.

Kolja Berger, Alexander Schulz, Benjamin Paaßen, Barbara Hammer

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

An EM transfer learning algorithm with applications in bionic hand prostheses.

Benjamin Paassen, Alexander Schulz, Janne Hahne, Barbara Hammer

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Echo State Networks as Novel Approach for Low-Cost Myoelectric Control.

Cosima Prahm, Alexander Schulz, Benjamin Paaßen, Oskar Aszmann, Barbara Hammer, Georg Dorffner

Proceedings of the Artificial Intelligence in Medicine, 2017

2016

Discriminative dimensionality reduction in kernel space.

Alexander Schulz, Barbara Hammer

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015

Using Discriminative Dimensionality Reduction to Visualize Classifiers.

Alexander Schulz, Andrej Gisbrecht, Barbara Hammer

Neural Process. Lett., 2015

Parametric nonlinear dimensionality reduction using kernel t-SNE.

Andrej Gisbrecht, Alexander Schulz, Barbara Hammer

Neurocomputing, 2015

Inferring Feature Relevances From Metric Learning.

Alexander Schulz, Bassam Mokbel, Michael Biehl, Barbara Hammer

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Discriminative dimensionality reduction for regression problems using the Fisher metric.

Alexander Schulz, Barbara Hammer

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Metric Learning in Dimensionality Reduction.

Alexander Schulz, Barbara Hammer

Proceedings of the ICPRAM 2015, 2015

Unsupervised Dimensionality Reduction for Transfer Learning.

Patrick Blöbaum, Alexander Schulz, Barbara Hammer

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Visualization of Regression Models Using Discriminative Dimensionality Reduction.

Alexander Schulz, Barbara Hammer

Proceedings of the Computer Analysis of Images and Patterns, 2015

2014

Relevance Learning for Dimensionality Reduction.

Alexander Schulz, Andrej Gisbrecht, Barbara Hammer

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Valid interpretation of feature relevance for linear data mappings.

Benoît Frénay, Daniela Hofmann, Alexander Schulz, Michael Biehl, Barbara Hammer

Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

2013

Using Nonlinear Dimensionality Reduction to Visualize Classifiers.

Alexander Schulz, Andrej Gisbrecht, Barbara Hammer

Proceedings of the Advances in Computational Intelligence, 2013

Applications of Discriminative Dimensionality Reduction.

Barbara Hammer, Andrej Gisbrecht, Alexander Schulz

Proceedings of the ICPRAM 2013, 2013

Discriminative Dimensionality Reduction for the Visualization of Classifiers.

Andrej Gisbrecht, Alexander Schulz, Barbara Hammer

Proceedings of the Pattern Recognition Applications and Methods - International Conference, 2013

2012

How to Visualize Large Data Sets?

Barbara Hammer, Andrej Gisbrecht, Alexander Schulz

Proceedings of the Advances in Self-Organizing Maps - 9th International Workshop, 2012