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ORCIDAlexander Schulz 0001
Person information
- affiliation: Bielefeld University, CITEC Centre of Excellence, Germany
Other persons with the same name
- Alexander Schulz 0002 — Technische Universität Wien, Austria
- Alexander Schulz 0003 — Hamburg University of Applied Sciences, Germany
- Alexander Schulz 0004 — University of Stuttgart, HLRS, Germany
- Alexander Schulz 0005 — Technische Universität Berlin, Germany
- Alexander Schulz 0006
![[0000-0003-2466-9086]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-2466-9086")
— Helmholtz Centre for Polar and Marine Research, Alfred Wegener Institute, Potsdam, Germany - Alexander Schulz 0007 — Reutlingen University, School of Informatics, Germany
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2020 – today
- 2024
[c30]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: 611-621- [c29]Sarah Schröder, Alexander Schulz, Fabian Hinder, Barbara Hammer:
Semantic Properties of Cosine Based Bias Scores for Word Embeddings. ICPRAM 2024: 160-168 - [c28]Sarah Schröder, Alexander Schulz, Barbara Hammer:
The SAME score: Improved cosine based measure for semantic bias. IJCNN 2024: 1-8 - [i13]Sarah Schröder, Alexander Schulz, Fabian Hinder, Barbara Hammer:
Semantic Properties of cosine based bias scores for word embeddings. CoRR abs/2401.15499 (2024) - [i12]Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer:
Debiasing Sentence Embedders through Contrastive Word Pairs. CoRR abs/2403.18555 (2024) - [i11]Isaac Roberts, Alexander Schulz, Luca Hermes, Barbara Hammer:
Targeted Visualization of the Backbone of Encoder LLMs. CoRR abs/2403.18872 (2024) - [i10]Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer:
Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in Transformers. CoRR abs/2404.01317 (2024) - 2023
- [j8]Johannes Kummert, Alexander Schulz, Barbara Hammer:
Metric Learning with Self-Adjusting Memory for Explaining Feature Drift. SN Comput. Sci. 4(4): 376 (2023) - [c27]Aleksei Liuliakov, Alexander Schulz, Luca Hermes, Barbara Hammer:
One-Class Intrusion Detection with Dynamic Graphs. ICANN (4) 2023: 537-549 - [c26]André Artelt, Alexander Schulz, Barbara Hammer:
"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction. ICPRAM 2023: 27-38 - [c25]Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer:
Debiasing Sentence Embedders Through Contrastive Word Pairs. ICPRAM 2023: 205-212 - [c24]Sarah Schröder, Alexander Schulz, Philip Kenneweg, Barbara Hammer:
So Can We Use Intrinsic Bias Measures or Not? ICPRAM 2023: 403-410 - [c23]Markus Vieth, Alexander Schulz, Barbara Hammer:
Extending Drift Detection Methods to Identify When Exactly the Change Happened. IWANN (1) 2023: 92-104 - [c22]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: 134-145 - [c21]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: 836-841 - [c20]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: 1292-1297 - 2022
- [j7]Benjamin Paaßen, Alexander Schulz, Barbara Hammer:
Reservoir stack machines. Neurocomputing 470: 352-364 (2022) - [j6]Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer:
Reservoir Memory Machines as Neural Computers. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2575-2585 (2022) - [c19]Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer:
Intelligent Learning Rate Distribution to Reduce Catastrophic Forgetting in Transformers. IDEAL 2022: 252-261 - [i9]Lisa Langnickel, Alexander Schulz, Barbara Hammer, Juliane Fluck:
BERT WEAVER: Using WEight AVERaging to Enable Lifelong Learning for Transformer-based Models. CoRR abs/2202.10101 (2022) - [i8]Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer:
The SAME score: Improved cosine based bias score for word embeddings. CoRR abs/2203.14603 (2022) - [i7]André Artelt, Alexander Schulz, Barbara Hammer:
"Why Here and Not There?" - Diverse Contrasting Explanations of Dimensionality Reduction. CoRR abs/2206.07391 (2022) - 2021
- [j5]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): 2114 (2021) - [i6]Benjamin Paaßen, Alexander Schulz, Barbara Hammer:
Reservoir Stack Machines. CoRR abs/2105.01616 (2021) - [i5]Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer:
Evaluating Metrics for Bias in Word Embeddings. CoRR abs/2111.07864 (2021) - 2020
- [c18]Benjamin Paassen, Alexander Schulz:
Reservoir memory machines. ESANN 2020: 567-572 - [c17]Alexander Schulz, Fabian Hinder, Barbara Hammer:
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction. IJCAI 2020: 2305-2311 - [i4]Benjamin Paassen, Alexander Schulz:
Reservoir memory machines. CoRR abs/2003.04793 (2020) - [i3]Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer:
Reservoir Memory Machines as Neural Computers. CoRR abs/2009.06342 (2020)
2010 – 2019
- 2019
- [i2]Alexander Schulz, Fabian Hinder, Barbara Hammer:
DeepView: Visualizing the behavior of deep neural networks in a part of the data space. CoRR abs/1909.09154 (2019) - 2018
- [j4]Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer:
Expectation maximization transfer learning and its application for bionic hand prostheses. Neurocomputing 298: 122-133 (2018) - [c16]Alexander Schulz, Jeffrey Frederic Queißer, Hisashi Ishihara, Minoru Asada:
Transfer Learning of Complex Motor Skills on the Humanoid Robot Affetto. ICDL-EPIROB 2018: 72-77 - 2017
- [b1]Alexander Schulz:
Discriminative dimensionality reduction: variations, applications, interpretations. Bielefeld University, Germany, 2017 - [j3]Alexander Schulz, Johannes Brinkrolf, Barbara Hammer:
Efficient kernelisation of discriminative dimensionality reduction. Neurocomputing 268: 34-41 (2017) - [c15]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: 338-342 - [c14]Benjamin Paassen, Alexander Schulz, Janne Hahne, Barbara Hammer:
An EM transfer learning algorithm with applications in bionic hand prostheses. ESANN 2017 - [c13]Kolja Berger, Alexander Schulz, Benjamin Paaßen, Barbara Hammer:
Linear supervised transfer learning for the large margin nearest neighbor classifier. SSCI 2017: 1-6 - [i1]Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer:
Expectation maximization transfer learning and its application for bionic hand prostheses. CoRR abs/1711.09256 (2017) - 2016
- [c12]Alexander Schulz, Barbara Hammer:
Discriminative dimensionality reduction in kernel space. ESANN 2016 - 2015
- [j2]Andrej Gisbrecht, Alexander Schulz, Barbara Hammer:
Parametric nonlinear dimensionality reduction using kernel t-SNE. Neurocomputing 147: 71-82 (2015) - [j1]Alexander Schulz, Andrej Gisbrecht, Barbara Hammer:
Using Discriminative Dimensionality Reduction to Visualize Classifiers. Neural Process. Lett. 42(1): 27-54 (2015) - [c11]Alexander Schulz, Barbara Hammer:
Visualization of Regression Models Using Discriminative Dimensionality Reduction. CAIP (2) 2015: 437-449 - [c10]Patrick Blöbaum, Alexander Schulz, Barbara Hammer:
Unsupervised Dimensionality Reduction for Transfer Learning. ESANN 2015 - [c9]Alexander Schulz, Barbara Hammer:
Metric Learning in Dimensionality Reduction. ICPRAM (1) 2015: 232-239 - [c8]Alexander Schulz, Barbara Hammer:
Discriminative dimensionality reduction for regression problems using the Fisher metric. IJCNN 2015: 1-8 - [c7]Alexander Schulz, Bassam Mokbel, Michael Biehl, Barbara Hammer:
Inferring Feature Relevances From Metric Learning. SSCI 2015: 1599-1606 - 2014
- [c6]Benoît Frénay, Daniela Hofmann, Alexander Schulz, Michael Biehl, Barbara Hammer:
Valid interpretation of feature relevance for linear data mappings. CIDM 2014: 149-156 - [c5]Alexander Schulz, Andrej Gisbrecht, Barbara Hammer:
Relevance Learning for Dimensionality Reduction. ESANN 2014 - 2013
- [c4]Barbara Hammer, Andrej Gisbrecht, Alexander Schulz:
Applications of Discriminative Dimensionality Reduction. ICPRAM 2013: 33-41 - [c3]Andrej Gisbrecht, Alexander Schulz, Barbara Hammer:
Discriminative Dimensionality Reduction for the Visualization of Classifiers. ICPRAM (Selected Papers) 2013: 39-56 - [c2]Alexander Schulz, Andrej Gisbrecht, Barbara Hammer:
Using Nonlinear Dimensionality Reduction to Visualize Classifiers. IWANN (1) 2013: 59-68 - 2012
- [c1]Barbara Hammer, Andrej Gisbrecht, Alexander Schulz:
How to Visualize Large Data Sets? WSOM 2012: 1-12
Coauthor Index
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