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» Equivalences on Observable Processes
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ICML
2008
IEEE
14 years 10 months ago
Fast Gaussian process methods for point process intensity estimation
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
John P. Cunningham, Krishna V. Shenoy, Maneesh Sah...
CGF
2010
106views more  CGF 2010»
13 years 10 months ago
Optical Image Processing Using Light Modulation Displays
We propose to enhance the capabilities of the human visual system by performing optical image processing directly on an observed scene. Unlike previous work which additively super...
Gordon Wetzstein, Wolfgang Heidrich, David Luebke
IROS
2009
IEEE
206views Robotics» more  IROS 2009»
14 years 4 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...

Book
361views
15 years 7 months ago
Introduction to Statistical Signal Processing
"A random or stochastic process is a mathematical model for a phenomenon that evolves in time in an unpredictable manner from the viewpoint of the observer. The phenomenon m...
R.M. Gray
APLAS
2010
ACM
13 years 10 months ago
Model Independent Order Relations for Processes
Semantic preorders between processes are usually applied in practice to model approximation or implementation relationships. For interactive models these preorders depend crucially...
Chaodong He