In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
With the increasing demand for spoken language interfaces in human-computer interactions, automatic recognition of emotional states from human speeches has become of increasing im...
Colour cues were used to obtain robust detection and tracking of people in relatively unconstrained dynamic scenes. Gaussian mixture models were used to estimate probability densi...
In this paper, a new theoretical framework based on hidden Markov model (HMM) and independent component analysis (ICA) mixture model is presented for content analysis of video, nam...