I argue that computer graphics can benefit from a deeper use of machine learning techniques. I give an overview of what learning has to offer the graphics community, with an emph...
We are designing a computational architecture for a "learning economy" based on personal software agents who represent users in a virtual society and assist them in find...
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
Coalition formation is a problem of great interest in AI, allowing groups of autonomous, individually rational agents to form stable teams. Automating the negotiations underlying ...
We present a novel extension to a recently proposed incremental learning algorithm for the word segmentation problem originally introduced in Goldwater (2006). By adding rejuvenat...