Proteomic profiling based on mass spectrometry is an important tool for studies at the protein and peptide level in medicine and health care. Thereby, the identification of releva...
Frank-Michael Schleif, Thomas Villmann, Barbara Ha...
In this paper we present UMiner, a new data mining system, which improves the quality of the data analysis results, handles uncertainty in the clustering & classification proce...
Christos Amanatidis, Maria Halkidi, Michalis Vazir...
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...