The rapid advances of evolutionary methods for multi-objective (MO) optimization poses the difficulty of keeping track of the developments in this field as well as selecting an app...
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
We experimented on task-level robot learning based on bi-directional theory. The via-point representation was used for ‘learning by watching’. In our previous work, we had a r...
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
There are many applications that demand large quantities of natural looking motion. It is difficult to synthesize motion that looks natural, particularly when it is people who mus...