Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
We present a method for designing efficient multigenic predictors with few probes and its application to the prediction of the response to preoperative chemotherapy in breast cance...
Background: Transcription factor binding site (TFBS) prediction is a difficult problem, which requires a good scoring function to discriminate between real binding sites and backg...
Markus T. Friberg, Peter von Rohr, Gaston H. Gonne...
We formalize and study business process systems that are centered around "business artifacts", or simply "artifacts". This approach focuses on data records, kn...
Alin Deutsch, Richard Hull, Fabio Patrizi, Victor ...
In this paper, we will propose a novel semi-automatic annotation scheme for video semantic classification. It is well known that the large gap between high-level semantics and low...