Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Many semi-supervised learning algorithms only
deal with binary classification. Their extension to the
multi-class problem is usually obtained by repeatedly
solving a set of bina...
Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs...
Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keer...
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance b...
Random Forests (RFs) have become commonplace
in many computer vision applications. Their
popularity is mainly driven by their high computational
efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...