This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
In this paper we study the identification of sparse interaction networks as a machine learning problem. Sparsity means that we are provided with a small data set and a high number...
Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ron...
Machine learning is an increasingly used computational tool within human-computer interaction research. While most researchers currently utilize an iterative approach to refining ...
It is argued that the analysis of the learner's generated log files during interactions with a learning environment is necessary to produce interpretative views of their activ...