169 citations · 186 across the 4 of their papers we have counts for
5 papers
Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation
Manuel Röder, Christoph Raab, Frank-Michael Schleif
Federated Learning has emerged as a leading paradigm for decentralized, privacy-preserving learning, particularly relevant in the era of interconnected edge devices equipped with s…
Federated Learning -- Methods, Applications and beyond
Moritz Heusinger, Christoph Raab, Fabrice Rossi +1
In recent years the applications of machine learning models have increased rapidly, due to the large amount of available data and technological progress.While some domains like web…
Transfer learning extensions for the probabilistic classification vector machine
Christoph Raab, Frank-Michael Schleif
Transfer learning is focused on the reuse of supervised learning models in a new context. Prominent applications can be found in robotics, image processing or web mining. In these…
Reactive Soft Prototype Computing for Concept Drift Streams
Christoph Raab, Moritz Heusinger, Frank-Michael Schleif
The amount of real-time communication between agents in an information system has increased rapidly since the beginning of the decade. This is because the use of these systems, e.…
Low-Rank Subspace Override for Unsupervised Domain Adaptation
Christoph Raab, Frank-Michael Schleif
Current supervised learning models cannot generalize well across domain boundaries, which is a known problem in many applications, such as robotics or visual classification. Domain…