We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
—The call-level performance modelling and evaluation of 3G cellular networks is important for the proper network dimensioning and efficient use of the network resources, such as ...
— Hierarchical state machines have proven to be a powerful tool for controlling autonomous robots due to their flexibility and modularity. For most real robot implementations, h...
We present a novel method for predictive modeling of human brain states from functional neuroimaging (fMRI) data. Extending the traditional canonical correlation analysis of discre...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
With the advent of XML we have seen a renewed interest in methods for computing the difference between trees. Methods that include heuristic elements play an important role in pr...
Tancred Lindholm, Jaakko Kangasharju, Sasu Tarkoma