We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...
We designed an activity-based prototyping process realized in the ActivityDesigner system that combines the theoretical framework of Activity-Centered Design with traditional iter...
Many decision problems can be modelled as adversarial constraint satisfaction, which allows us to integrate methods from AI game playing. In particular, by using the idea of oppone...
The ability to represent non-height-field mesostructure details is of great importance for rendering complex surface patterns, such as weave and multilayer structures. Currently,...