2 papers
cs.LG2020
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare
Ali Burak Ünal, Mete Akgün, Nico Pfeifer
To train sophisticated machine learning models one usually needs many training samples. Especially in healthcare settings these samples can be very expensive, meaning that one inst…
stat.ML2018
An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes
Nora K. Speicher, Nico Pfeifer
Due to the complexity of cancer, clustering algorithms have been used to disentangle the observed heterogeneity and identify cancer subtypes that can be treated specifically. While…