We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Digital games are becoming a rising trend in eLearning due to their potential educational benefits. However, their application is hindered by issues such as their high production ...
Javier Torrente, Pablo Moreno-Ger, Baltasar Fern&a...
An articulatory speech synthesizer comprising a three-dimensional vocal tract model and a gesture-based concept for control of articulatory movements is introduced and discussed in...