The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...
In this paper we propose an approach for action recognition based on a vocabulary of local motion-appearance features and fast approximate search in a large number of trees. Large...
We present a transformation scheme that mediates between description logics (DL) or RDF-encoded ontologies and type hierarchies in feature logics (FL). The DL-to-FL direction is i...
Adaptive stimulus design methods can potentially improve the efficiency of sensory neurophysiology experiments significantly; however, designing optimal stimulus sequences in re...
Jeremy Lewi, David M. Schneider, Sarah M. N. Wooll...
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...