Both teaching and learning multithreaded ing are complex tasks, due to the abstraction of the concepts, the non-determinism of the scheduler, the impossibility of using classical s...
Giovanni Malnati, Caterina Maria Cuva, Claudia Bar...
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Abstract. In recent years the problem of object recognition has received considerable attention from both the machine learning and computer vision communities. The key challenge of...
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...