169 citations · 177 across the 2 of their papers we have counts for
5 papers
Complex-valued embeddings of generic proximity data
Maximilian Münch, Michiel Straat, Michael Biehl +1
Proximities are at the heart of almost all machine learning methods. If the input data are given as numerical vectors of equal lengths, euclidean distance, or a Hilbertian inner pr…
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…
Probabilistic classifiers with low rank indefinite kernels
Frank-Michael Schleif, Andrej Gisbrecht, Peter Tino
Indefinite similarity measures can be frequently found in bio-informatics by means of alignment scores, but are also common in other fields like shape measures in image retrieval.…