Tracking heart motion plays an essential role in the diagnosis of cardiovascular diseases. This study investigates overlap priors for variational tracking of the Left Ventricle (LV...
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
In this paper, we propose an embedding method to seek an optimal low-dimensional manifold describing the intrinsical pose variations and to provide an identity-independent head pos...