Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
We consider the problem of automatically learning color enhancements from a small set of sample color pairs, and describing the enhancement by a three-dimensional look-uptable tha...
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Anomaly detection has received much attention within the literature as a means of determining, in an unsupervised manner, whether a learning domain has changed in a fundamental way...