Alexander Schulz

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 36

Top Topics

Transfer Learning

Dimensionality Reduction

Expectation Maximization

Top Venues

Publications

Isaac Roberts, Alexander Schulz, Luca Hermes, Barbara Hammer
Targeted Visualization of the Backbone of Encoder LLMs. CoRR (2024)
Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer
Debiasing Sentence Embedders through Contrastive Word Pairs. CoRR (2024)
Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer
Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in Transformers. CoRR (2024)
Sarah Schröder, Alexander Schulz, Fabian Hinder, Barbara Hammer
Semantic Properties of Cosine Based Bias Scores for Word Embeddings. ICPRAM (2024)
Nils Grimmelsmann, Malte Mechtenberg, Markus Vieth, Alexander Schulz, Barbara Hammer, Axel Schneider
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. BIOSTEC (1) (2024)
Sarah Schröder, Alexander Schulz, Fabian Hinder, Barbara Hammer
Semantic Properties of cosine based bias scores for word embeddings. CoRR (2024)
Johannes Kummert, Alexander Schulz, Barbara Hammer
Metric Learning with Self-Adjusting Memory for Explaining Feature Drift. SN Comput. Sci. 4 (4) (2023)
Sarah Schröder, Alexander Schulz, Philip Kenneweg, Barbara Hammer
So Can We Use Intrinsic Bias Measures or Not? ICPRAM (2023)
Johannes Kummert, Alexander Schulz, Robert Feldhans, Moriz Habigt, Maike Stemmler, Christina Kohler, Dirk Abel, Rolf Rossaint, Barbara Hammer
Generating Cardiovascular Data to Improve Training of Assistive Heart Devices. SSCI (2023)
Sarah Schröder, Alexander Schulz, Ivan Tarakanov, Robert Feldhans, Barbara Hammer
Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation. IWANN (1) (2023)
André Artelt, Alexander Schulz, Barbara Hammer
"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction. ICPRAM (2023)
Markus Vieth, Alexander Schulz, Barbara Hammer
Extending Drift Detection Methods to Identify When Exactly the Change Happened. IWANN (1) (2023)
Robert Feldhans, Alexander Schulz, Johannes Kummert, Moriz Habigt, Maike Stemmler, Christina Kohler, Dirk Abel, Rolf Rossaint, Barbara Hammer
Data Augmentation for Cardiovascular Time Series Data Using WaveNet. SSCI (2023)
Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer
Debiasing Sentence Embedders Through Contrastive Word Pairs. ICPRAM (2023)
Lisa Langnickel, Alexander Schulz, Barbara Hammer, Juliane Fluck
BERT WEAVER: Using WEight AVERaging to Enable Lifelong Learning for Transformer-based Models. CoRR (2022)
Benjamin Paaßen, Alexander Schulz, Barbara Hammer
Reservoir stack machines. Neurocomputing 470 (2022)
Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer
The SAME score: Improved cosine based bias score for word embeddings. CoRR (2022)
Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer
Intelligent Learning Rate Distribution to Reduce Catastrophic Forgetting in Transformers. IDEAL (2022)
André Artelt, Alexander Schulz, Barbara Hammer
"Why Here and Not There?" - Diverse Contrasting Explanations of Dimensionality Reduction. CoRR (2022)
Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer
Reservoir Memory Machines as Neural Computers. IEEE Trans. Neural Networks Learn. Syst. 33 (6) (2022)
Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer
Evaluating Metrics for Bias in Word Embeddings. CoRR (2021)
Benjamin Paaßen, Alexander Schulz, Barbara Hammer
Reservoir Stack Machines. CoRR (2021)
Johannes Kummert, Alexander Schulz, Tim Redick, Nassim Ayoub, Ali Modabber, Dirk Abel, Barbara Hammer
Efficient Reject Options for Particle Filter Object Tracking in Medical Applications. Sensors 21 (6) (2021)
Alexander Schulz, Fabian Hinder, Barbara Hammer
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction. IJCAI (2020)
Benjamin Paassen, Alexander Schulz
Reservoir memory machines. ESANN (2020)
Benjamin Paassen, Alexander Schulz
Reservoir memory machines. CoRR (2020)
Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer
Reservoir Memory Machines as Neural Computers. CoRR (2020)
Alexander Schulz, Fabian Hinder, Barbara Hammer
DeepView: Visualizing the behavior of deep neural networks in a part of the data space. CoRR (2019)
Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer
Expectation maximization transfer learning and its application for bionic hand prostheses. Neurocomputing 298 (2018)
Alexander Schulz, Jeffrey Frederic Queißer, Hisashi Ishihara, Minoru Asada
Transfer Learning of Complex Motor Skills on the Humanoid Robot Affetto. ICDL-EPIROB (2018)
Kolja Berger, Alexander Schulz, Benjamin Paaßen, Barbara Hammer
Linear supervised transfer learning for the large margin nearest neighbor classifier. SSCI (2017)
Alexander Schulz, Johannes Brinkrolf, Barbara Hammer
Efficient kernelisation of discriminative dimensionality reduction. Neurocomputing 268 (2017)
Benjamin Paassen, Alexander Schulz, Janne Hahne, Barbara Hammer
An EM transfer learning algorithm with applications in bionic hand prostheses. ESANN (2017)
Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer
Expectation maximization transfer learning and its application for bionic hand prostheses. CoRR (2017)
Cosima Prahm, Alexander Schulz, Benjamin Paaßen, Oskar Aszmann, Barbara Hammer, Georg Dorffner
Echo State Networks as Novel Approach for Low-Cost Myoelectric Control. AIME (2017)
Alexander Schulz, Barbara Hammer
Discriminative dimensionality reduction in kernel space. ESANN (2016)
Alexander Schulz, Barbara Hammer
Metric Learning in Dimensionality Reduction. ICPRAM (1) (2015)
Alexander Schulz, Barbara Hammer
Discriminative dimensionality reduction for regression problems using the Fisher metric. IJCNN (2015)
Patrick Blöbaum, Alexander Schulz, Barbara Hammer
Unsupervised Dimensionality Reduction for Transfer Learning. ESANN (2015)
Alexander Schulz, Barbara Hammer
Visualization of Regression Models Using Discriminative Dimensionality Reduction. CAIP (2) (2015)
Andrej Gisbrecht, Alexander Schulz, Barbara Hammer
Parametric nonlinear dimensionality reduction using kernel t-SNE. Neurocomputing 147 (2015)
Alexander Schulz, Bassam Mokbel, Michael Biehl, Barbara Hammer
Inferring Feature Relevances From Metric Learning. SSCI (2015)
Alexander Schulz, Andrej Gisbrecht, Barbara Hammer
Using Discriminative Dimensionality Reduction to Visualize Classifiers. Neural Process. Lett. 42 (1) (2015)
Alexander Schulz, Andrej Gisbrecht, Barbara Hammer
Relevance Learning for Dimensionality Reduction. ESANN (2014)
Benoît Frénay, Daniela Hofmann, Alexander Schulz, Michael Biehl, Barbara Hammer
Valid interpretation of feature relevance for linear data mappings. CIDM (2014)
Barbara Hammer, Andrej Gisbrecht, Alexander Schulz
Applications of Discriminative Dimensionality Reduction. ICPRAM (2013)
Alexander Schulz, Andrej Gisbrecht, Barbara Hammer
Using Nonlinear Dimensionality Reduction to Visualize Classifiers. IWANN (1) (2013)
Andrej Gisbrecht, Alexander Schulz, Barbara Hammer
Discriminative Dimensionality Reduction for the Visualization of Classifiers. ICPRAM (Selected Papers) (2013)
Barbara Hammer, Andrej Gisbrecht, Alexander Schulz
How to Visualize Large Data Sets? WSOM (2012)