Aspects in classification learning-Review of recent developments in Learning Vector Quantization
Classification is one of the most frequent tasks in machine learning. However, the variety of
classification tasks as well as classifier methods is huge. Thus the question is coming up …
classification tasks as well as classifier methods is huge. Thus the question is coming up …
Median variants of learning vector quantization for learning of dissimilarity data
Exemplar based techniques such as affinity propagation represent data in terms of typical
exemplars. This has two benefits:(i) the resulting models are directly interpretable by …
exemplars. This has two benefits:(i) the resulting models are directly interpretable by …
Sequence learning in unsupervised and supervised vector quantization using Hankel matrices
M Mohammadi, M Biehl, A Villmann… - … Conference on Artificial …, 2017 - Springer
In the present contribution we consider sequence learning by means of unsupervised and
supervised vector quantization, which should be invariant regarding to shifts in the …
supervised vector quantization, which should be invariant regarding to shifts in the …
Hebbian learning approaches based on general inner products and distance measures in non-Euclidean spaces
M Lange - 2019 - research.rug.nl
The topic of this thesis is to define a unified and generalized scheme for Hebbian
approaches in non-Euclidean spaces for unsupervised and supervised learning. This can …
approaches in non-Euclidean spaces for unsupervised and supervised learning. This can …