This paper introduces the concept of eigen-dynamics and proposes an eigen dynamics analysis (EDA) method to learn the dynamics of natural hand motion from labelled sets of motion ...
We generalise the optimisation technique of dynamic programming for discretetime systems with an uncertain gain function. We assume that uncertainty about the gain function is des...
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Abstract. We propose a new approach to modeling time-varying relational data such as e-mail transactions based on a dynamic extension of matrix factorization. To estimate effectiv...
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...