In the problem of probability forecasting the learner’s goal is to output, given a training set and a new object, a suitable probability measure on the possible values of the ne...
We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-bui...
Benjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Ko...
Model abstraction using metamodeling has demonstrated the capability to facilitate software reuse, large scale model integration, verification, and validation. Once restricted to...
Molecular sequence megaclassification is a technique for automated protein sequence analysis and annotation. Implementation of the method has been limited by the need to store and...
— Imputation of missing data is important in many areas, such as reducing non-response bias in surveys and maintaining medical documentation. Estimating the uncertainty inherent ...