We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
A new statistical channel model known as the Multiple Scatterer Channel (MSC) is developed to capture the time variations of both line-of-sight (LOS) and non-line-of-sight (NLOS) f...
We present a methodology for learning spline-based probabilistic models for sets of contours, proposing a new Monte Carlo variant of the EM algorithm to estimate the parameters of...
Abstract. This paper proposes a new adaptive wavelet-based Magnetic Resonance images denoising algorithm. A Rician distribution for background-noise modelling is introduced and a M...
The two parameter Poisson-Dirichlet process is also known as the PitmanYor Process and related to the Chinese Restaurant Process, is a generalisation of the Dirichlet Process, and...