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NIPS
2004
15 years 8 months ago
Learning first-order Markov models for control
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
Pieter Abbeel, Andrew Y. Ng
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
15 years 7 months ago
An EDA based on local markov property and gibbs sampling
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
Siddhartha Shakya, Roberto Santana
NECO
2007
108views more  NECO 2007»
15 years 6 months ago
Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal Theories
We propose a Markov process model for spike-frequency adapting neural ensembles which synthesizes existing mean-adaptation approaches, population density methods, and inhomogeneou...
Eilif Mueller, Lars Buesing, Johannes Schemmel, Ka...
IJMMSC
2010
62views more  IJMMSC 2010»
15 years 1 months ago
Conditional Processes Induced by Birth and Death Processes
For birth and death processes with finite state space consisting of N + 1 points (N 2), we consider stochastic processes induced by conditioning on hitting the right boundary poi...
Masaru Iizuka, Matsuyo Tomisaki
CIKM
2009
Springer
16 years 1 months ago
A general markov framework for page importance computation
We propose a General Markov Framework for computing page importance. Under the framework, a Markov Skeleton Process is used to model the random walk conducted by the web surfer on...
Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Ha...