Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
As grid computation systems become larger and more complex, manually diagnosing failures in jobs becomes impractical. Recently, machine-learning techniques have been proposed to d...
In this paper we study a paradigm to generalize online classification algorithms for binary classification problems to multiclass problems. The particular hypotheses we investig...
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
The focus of this work is on the estimation of quality of service (QoS) parameters seen by an application. Our proposal is based on end-to-end active measurements and statistical ...