Christoph Raab

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 27

Top Topics

Dimensionality Reduction

Domain Adaptation

Top Venues

Publications

Manuel Röder, Maximilian Münch, Christoph Raab, Frank-Michael Schleif
Crossing Domain Borders with Federated Few-Shot Adaptation. ICPRAM (2024)
Maximilian Münch, Manuel Röder, Simon Heilig, Christoph Raab, Frank-Michael Schleif
Static and adaptive subspace information fusion for indefinite heterogeneous proximity data. Neurocomputing 555 (2023)
Maximilian Münch, Christoph Raab, Simon Heilig, Manuel Röder, Frank-Michael Schleif
Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification. ESANN (2022)
Christoph Raab, Manuel Röder, Frank-Michael Schleif
Domain adversarial tangent subspace alignment for explainable domain adaptation. Neurocomputing 506 (2022)
Moritz Heusinger, Christoph Raab, Frank-Michael Schleif
Dimensionality reduction in the context of dynamic social media data streams. Evol. Syst. 13 (3) (2022)
Moritz Heusinger, Christoph Raab, Frank-Michael Schleif
Passive concept drift handling via variations of learning vector quantization. Neural Comput. Appl. 34 (1) (2022)
Moritz Heusinger, Christoph Raab, Fabrice Rossi, Frank-Michael Schleif
Federated Learning - Methods, Applications and beyond. CoRR (2022)
Christoph Raab, Sascha Saralajew, Frank-Michael Schleif
Domain Adversarial Tangent Learning Towards Interpretable Domain Adaptation. ESANN (2021)
Moritz Heusinger, Christoph Raab, Fabrice Rossi, Frank-Michael Schleif
Federated Learning - Methods, Applications and beyond. ESANN (2021)
Christoph Raab, Moritz Heusinger, Frank-Michael Schleif
Reactive Soft Prototype Computing for Concept Drift Streams. CoRR (2020)
Christoph Raab, Philipp Väth, Peter Meier, Frank-Michael Schleif
Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks. ACCV (3) (2020)
Frank-Michael Schleif, Christoph Raab, Peter Tiño
Sparsification of core set models in non-metric supervised learning. Pattern Recognit. Lett. 129 (2020)
Maximilian Münch, Christoph Raab, Michael Biehl, Frank-Michael Schleif
Data-Driven Supervised Learning for Life Science Data. Frontiers Appl. Math. Stat. 6 (2020)
Christoph Raab, Frank-Michael Schleif
Low-Rank Subspace Override for Unsupervised Domain Adaptation. KI (2020)
Christoph Raab, Moritz Heusinger, Frank-Michael Schleif
Reactive Soft Prototype Computing for Concept Drift Streams. Neurocomputing 416 (2020)
Maximilian Münch, Christoph Raab, Michael Biehl, Frank-Michael Schleif
Structure Preserving Encoding of Non-euclidean Similarity Data. ICPRAM (2020)
Christoph Raab, Frank-Michael Schleif
Transfer learning extensions for the probabilistic classification vector machine. CoRR (2020)
Christoph Raab, Frank-Michael Schleif
Transfer learning extensions for the probabilistic classification vector machine. Neurocomputing 397 (2020)
Maximilian Münch, Christoph Raab, Frank-Michael Schleif
Encoding of Indefinite Proximity Data: A Structure Preserving Perspective. ICPRAM (Revised Selected Papers) (2020)
Christoph Raab, Peter Meier, Frank-Michael Schleif
Domain Invariant Representations with Deep Spectral Alignment. ESANN (2020)
Moritz Heusinger, Christoph Raab, Frank-Michael Schleif
Analyzing Dynamic Social Media Data via Random Projection - A New Challenge for Stream Classifiers. EAIS (2020)
Christoph Raab, Moritz Heusinger, Frank-Michael Schleif
Reactive Soft Prototype Computing for frequent reoccurring Concept Drift. ESANN (2019)
Christoph Raab, Frank-Michael Schleif
Domain Adaptation via Low-Rank Basis Approximation. CoRR (2019)
Moritz Heusinger, Christoph Raab, Frank-Michael Schleif
Passive Concept Drift Handling via Momentum Based Robust Soft Learning Vector Quantization. WSOM+ (2019)
Christoph Raab, Frank-Michael Schleif
Sparse Transfer Classification for Text Documents. KI (2018)
Christoph Raab, Frank-Michael Schleif
Transfer learning for the probabilistic classification vector machine. COPA (2018)
Frank-Michael Schleif, Christoph Raab, Peter Tiño
Sparsification of Indefinite Learning Models. S+SSPR (2018)