The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
The Extended Baum-Welch (EBW) Transformations is one of a variety of techniques to estimate parameters of Gaussian mixture models. In this paper, we provide a theoretical framewor...
Dimitri Kanevsky, Tara N. Sainath, Bhuvana Ramabha...
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...