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JSSPP
2004
Springer
14 years 2 months ago
Parallel Computer Workload Modeling with Markov Chains
Abstract. In order to evaluate different scheduling strategies for parallel computers, simulations are often executed. As the scheduling quality highly depends on the workload tha...
Baiyi Song, Carsten Ernemann, Ramin Yahyapour
AMC
2008
99views more  AMC 2008»
13 years 9 months ago
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Roderick V. N. Melnik
ECML
2006
Springer
14 years 15 days ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...
ICASSP
2010
IEEE
13 years 9 months ago
Variational nonparametric Bayesian Hidden Markov Model
The Hidden Markov Model (HMM) has been widely used in many applications such as speech recognition. A common challenge for applying the classical HMM is to determine the structure...
Nan Ding, Zhijian Ou
PRDC
2006
IEEE
14 years 2 months ago
Detecting and Exploiting Symmetry in Discrete-state Markov Models
Dependable systems are usually designed with multiple instances of components or logical processes, and often possess symmetries that may be exploited in model-based evaluation. T...
W. Douglas Obal II, Michael G. McQuinn, William H....