This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
Modeling human behavior can be complicated and expensive. To be able to reduce costs, new methodologies and tools must be developed that automate the creation of human behavior mo...
Recent works about the activity-oriented approach et educational modeling languages ask questions about the pedagogical scenario concept. The aim of this paper is to define the fo...
We consider the general, widely applicable problem of selecting from n real-valued random variables a subset of size m of those with the highest means, based on as few samples as ...
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...