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» Approximate inference by Markov chains on union spaces
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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. ...
IPPS
2008
IEEE
14 years 2 months ago
Reducing the run-time of MCMC programs by multithreading on SMP architectures
The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Mont...
Jonathan M. R. Byrd, Stephen A. Jarvis, A. H. Bhal...
CALCO
2007
Springer
100views Mathematics» more  CALCO 2007»
14 years 1 months ago
Applications of Metric Coinduction
Metric coinduction is a form of coinduction that can be used to establish properties of objects constructed as a limit of finite approximations. One can prove a coinduction step s...
Dexter Kozen, Nicholas Ruozzi
CDC
2008
IEEE
120views Control Systems» more  CDC 2008»
14 years 2 months ago
Approximate abstractions of discrete-time controlled stochastic hybrid systems
ate Abstractions of Discrete-Time Controlled Stochastic Hybrid Systems Alessandro D’Innocenzo, Alessandro Abate, and Maria D. Di Benedetto — This work proposes a procedure to c...
Alessandro D'Innocenzo, Alessandro Abate, Maria Do...
CDC
2009
IEEE
132views Control Systems» more  CDC 2009»
14 years 11 days ago
Q-learning and Pontryagin's Minimum Principle
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
Prashant G. Mehta, Sean P. Meyn