Many classification algorithms use the concept of distance or similarity between patterns. Previous work has shown that it is advantageous to optimize general Euclidean distances (...
Machine learning methods that can use additional knowledge in their inference process are central to the development of integrative bioinformatics. Inclusion of background knowled...
Minca Mramor, Marko Toplak, Gregor Leban, Tomaz Cu...
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
As applications are developed, functional tests ensure they continue to function as expected. Nowadays, functional testing is mostly done manually, with human testers verifying a ...
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...