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NN
2010
Springer
125views Neural Networks» more  NN 2010»
13 years 7 months ago
Parameter-exploring policy gradients
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...
Frank Sehnke, Christian Osendorfer, Thomas Rü...
ICC
2007
IEEE
107views Communications» more  ICC 2007»
14 years 1 months ago
A New Multiple Scatterer Model for Fixed Indoor Wireless Communication Channels
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...
Paisarn Sonthikorn, Ozan K. Tonguz
ICPR
2010
IEEE
13 years 11 months ago
Learning Probabilistic Models of Contours
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...
Laure Amate, Maria João Rendas
DICTA
2003
13 years 10 months ago
Adaptive Magnetic Resonance Image Denoising Using Mixture Model and Wavelet Shrinkage
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...
Lei Jiang, Wenhui Yang
CORR
2010
Springer
168views Education» more  CORR 2010»
13 years 9 months ago
A Bayesian Review of the Poisson-Dirichlet Process
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...
Wray L. Buntine, Marcus Hutter