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Christoph Raab
Christoph Raab
University of applied science Würzburg-Schweinfurt
Verified email at fhws.de - Homepage
Title
Cited by
Cited by
Year
Reactive soft prototype computing for concept drift streams
C Raab, M Heusinger, FM Schleif
Neurocomputing 416, 340-351, 2020
1232020
Passive concept drift handling via variations of learning vector quantization
M Heusinger, C Raab, FM Schleif
Neural Computing and Applications 34 (1), 89-100, 2022
212022
Passive concept drift handling via momentum based robust soft learning vector quantization
M Heusinger, C Raab, FM Schleif
Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering …, 2020
182020
Bridging adversarial and statistical domain transfer via spectral adaptation networks
C Raab, P Vath, P Meier, FM Schleif
Proceedings of the Asian Conference on Computer Vision, 2020
132020
Reactive Soft Prototype Computing for frequent reoccurring Concept Drift.
C Raab, M Heusinger, FM Schleif
ESANN, 2019
132019
Data-driven supervised learning for life science data
M Münch, C Raab, M Biehl, FM Schleif
Frontiers in Applied Mathematics and Statistics 6, 553000, 2020
102020
Transfer learning extensions for the probabilistic classification vector machine
C Raab, FM Schleif
Neurocomputing 397, 320-330, 2020
82020
Domain adversarial tangent subspace alignment for explainable domain adaptation
C Raab, M Röder, FM Schleif
Neurocomputing 506, 418-429, 2022
72022
PROVAL: A framework for comparison of protein sequence embeddings
P Väth, M Münch, C Raab, FM Schleif
Journal of Computational Mathematics and Data Science 3, 100044, 2022
72022
Dimensionality reduction in the context of dynamic social media data streams
M Heusinger, C Raab, FM Schleif
Evolving Systems 13 (3), 387-401, 2022
72022
Low-rank subspace override for unsupervised domain adaptation
C Raab, FM Schleif
KI 2020: Advances in Artificial Intelligence: 43rd German Conference on AI …, 2020
72020
Sparsification of core set models in non-metric supervised learning
FM Schleif, C Raab, P Tino
Pattern Recognition Letters 129, 1-7, 2020
72020
Transfer learning for the probabilistic classification vector machine
C Raab, FM Schleif
Conformal and probabilistic prediction and applications, 187-200, 2018
62018
Sparse transfer classification for text documents
C Raab, FM Schleif
KI 2018: Advances in Artificial Intelligence: 41st German Conference on AI …, 2018
62018
Analyzing dynamic social media data via random projection-a new challenge for stream classifiers
M Heusinger, C Raab, FM Schleif
2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 1-8, 2020
52020
Structure preserving encoding of non-euclidean similarity data
M Münch, C Raab, M Biehl, FM Schleif
The 9th International Conference on Pattern Recognition Applications and …, 2020
52020
Federated Learning--Methods, Applications and beyond
M Heusinger, C Raab, F Rossi, FM Schleif
arXiv preprint arXiv:2212.11729, 2022
32022
Encoding of indefinite proximity data: A structure preserving perspective
M Münch, C Raab, FM Schleif
Pattern Recognition Applications and Methods: 9th International Conference …, 2020
32020
Sparsification of indefinite learning models
FM Schleif, C Raab, P Tino
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2018
32018
Domain adaptation via low-rank basis approximation
C Raab, FM Schleif
22019
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