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JMLR
2010
152views more  JMLR 2010»
13 years 2 months ago
Bayesian Generalized Kernel Models
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
ICML
2008
IEEE
14 years 8 months ago
A worst-case comparison between temporal difference and residual gradient with linear function approximation
Residual gradient (RG) was proposed as an alternative to TD(0) for policy evaluation when function approximation is used, but there exists little formal analysis comparing them ex...
Lihong Li
CSDA
2006
169views more  CSDA 2006»
13 years 8 months ago
Generalized structured additive regression based on Bayesian P-splines
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Ba...
Andreas Brezger, Stefan Lang
TCOM
2010
98views more  TCOM 2010»
13 years 2 months ago
Convolutionally Coded Transmission over Markov-Gaussian Channels: Analysis and Decoding Metrics
It has been widely acknowledged that the aggregate interference at the receiver for various practical communication channels can often deviate markedly from the classical additive ...
Jeebak Mitra, Lutz H.-J. Lampe
IJCAI
2001
13 years 9 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell