Alexander Schulz
Alexander Schulz
Technical Faculty, CITEC, Bielefeld University
Geverifieerd e-mailadres voor techfak.uni-bielefeld.de - Homepage
Geciteerd door
Geciteerd door
Parametric nonlinear dimensionality reduction using kernel t-SNE
A Gisbrecht, A Schulz, B Hammer
Neurocomputing, 2015
Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis After Electrode Shift
Cosima Prahm, B Paassen, A Schulz, B Hammer, O Aszmann
Converging Clinical and Engineering Research on Neurorehabilitation II, 153-157, 2017
Counteracting electrode shifts in upper-limb prosthesis control via transfer learning
C Prahm, A Schulz, B Paaßen, J Schoisswohl, E Kaniusas, G Dorffner, ...
IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (5 …, 2019
Expectation maximization transfer learning and its application for bionic hand prostheses
B Paaßen, A Schulz, J Hahne, B Hammer
Neurocomputing 298, 122-133, 2018
Using discriminative dimensionality reduction to visualize classifiers
A Schulz, A Gisbrecht, B Hammer
Neural Processing Letters 42 (1), 27-54, 2015
Deepview: Visualizing classification boundaries of deep neural networks as scatter plots using discriminative dimensionality reduction
A Schulz, F Hinder, B Hammer
(IJCAI 2020) Proceedings of the Twenty-Ninth International Conference on …, 2019
Valid interpretation of feature relevance for linear data mappings
B Fránay, D Hofmann, A Schulz, M Biehl, B Hammer
Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on, 2014
Tissue-and development-stage–specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples
A Panda, A Yadav, H Yeerna, A Singh, M Biehl, M Lux, A Schulz, T Klecha, ...
Nucleic acids research 48 (13), 7079-7098, 2020
Linear Supervised Transfer Learning for Generalized Matrix LVQ
B Paaßen, A Schulz, B Hammer
Proceedings of the Workshop New Challenges in Neural Computation 2016, 2016
How to Visualize Large Data Sets?
B Hammer, A Gisbrecht, A Schulz
Advances in Self-Organizing Maps, 2013
Inferring feature relevances from metric learning
A Schulz, B Mokbel, M Biehl, B Hammer
Computational Intelligence, 2015 IEEE Symposium Series on, 2015
Unsupervised Dimensionality Reduction for Transfer Learning
P Blöbaum, A Schulz, B Hammer
Proceedings. 23rd European Symposium on Artificial Neural Networks …, 2015
How to visualize a classifier
A Schulz, A Gisbrecht, K Bunte, B Hammer
New Challenges in Neural Computation, 2012
Reservoir memory machines
B Paaßen, A Schulz
arXiv preprint arXiv:2003.04793, 2020
Efficient kernelisation of discriminative dimensionality reduction
A Schulz, J Brinkrolf, B Hammer
Neurocomputing 268, 34-41, 2017
Echo state networks as novel approach for low-cost myoelectric control
C Prahm, A Schulz, B Paaßen, O Aszmann, B Hammer, G Dorffner
Artificial Intelligence in Medicine: 16th Conference on Artificial …, 2017
An EM transfer learning algorithm with applications in bionic hand prostheses
B Paaßen, A Schulz, J Hahne, B Hammer
Proceedings of the 25th european symposium on artificial neural networks …, 2017
Evaluating Metrics for Bias in Word Embeddings
S Schröder, A Schulz, P Kenneweg, R Feldhans, F Hinder, B Hammer
arXiv preprint arXiv:2111.07864, 2021
Reservoir memory machines as neural computers
B Paaßen, A Schulz, TC Stewart, B Hammer
IEEE Transactions on Neural Networks and Learning Systems, 2021
Discriminative dimensionality reduction for regression problems using the fisher metric
A Schulz, B Hammer
Neural Networks (IJCNN), 2015 International Joint Conference on, 2015
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