We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
We present a new method for estimating the expected return of a POMDP from experience. The estimator does not assume any knowledge of the POMDP, can estimate the returns for finit...
The Desktop History Tool presents users with a summary of the data they worked with throughout past days and weeks. The user’s own interaction history provides an invaluable sel...
This paper describes an all level approach on statistical natural language translation (SNLT). Without any predefined knowledge the system learns a statistical translation lexicon...
A highly successful active contour implementation, for the automatic segmentation of cervical cell nuclei, is shown to lend itself well to a framework that further increases its s...