We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Early diagnosis and treatment of patients at high risk of developing fragility fractures is crucial in the management of osteoporosis. In this paper we propose to estimate the ris...
Benchmarking pattern recognition, machine learning and data mining methods commonly relies on real-world data sets. However, there are some disadvantages in using real-world data....
Janick V. Frasch, Aleksander Lodwich, Faisal Shafa...
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...