This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents ...
We discuss the problem of finding a good state representation in stochastic systems with observations. We develop a duality theory that generalizes existing work in predictive sta...
Christopher Hundt, Prakash Panangaden, Joelle Pine...
We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the obje...
We present a general method for explaining individual predictions of classification models. The method is based on fundamental concepts from coalitional game theory and prediction...
Boosting has established itself as a successful technique for decreasing the generalization error of classification learners by basing predictions on ensembles of hypotheses. Whil...