Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Multi-label classification is a popular learning task. However, some of the algorithms that learn from multi-label data, can only output a score for each label, so they cannot be r...
Marios Ioannou, George Sakkas, Grigorios Tsoumakas...
The vast majority of medical computer-based training (CBT) systems aim at problem-oriented case based training. A crucial issue in the design of CBT systems is the selection of ap...
Reproducing and learning from failures in deployed software is costly and difficult. Those activities can be facilitated, however, if the circumstances leading to a failure are p...
Sebastian G. Elbaum, Satya Kanduri, Anneliese Amsc...
This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...