We study the problem of learning using combinations of machines. In particular we present new theoretical bounds on the generalization performance of voting ensembles of kernel ma...
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
Using open e-learning platforms as a tool to support the learning process has become an international tendency. Specially, in order to motivate the achievement of desired competen...
Laura Mancera Valetts, Silvia Baldiris Navarro, Ra...
Statistical machine learning continues to show promise as a tool for addressing complex problems in a variety of domains. An increasing number of developers are therefore looking ...
Kayur Patel, James Fogarty, James A. Landay, Bever...
— Machine learning has made great progress during the last decades and is being deployed in a wide range of applications. However, current machine learning techniques are far fro...