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» Building a Stochastic Dynamic Model of Application Use
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126
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ECML
2006
Springer
15 years 8 months 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...
138
Voted
DATE
2010
IEEE
163views Hardware» more  DATE 2010»
15 years 9 months ago
Efficient High-Level modeling in the networking domain
-- Starting Electronic System Level (ESL) design flows with executable High-Level Models (HLMs) has the potential to sustainably improve productivity. However, writing good HLMs fo...
Christian Zebelein, Joachim Falk, Christian Haubel...
126
Voted
SIGADA
2005
Springer
15 years 10 months ago
Temporal skeletons for verifying time
This paper presents an intermediate notation used in a framework for verification of real-time properties. The framework aims at overcoming the need for the framework user to hav...
Gustaf Naeser, Kristina Lundqvist, Lars Asplund
CMSB
2006
Springer
15 years 8 months ago
Probabilistic Model Checking of Complex Biological Pathways
Abstract. Probabilistic model checking is a formal verification technique that has been successfully applied to the analysis of systems from a broad range of domains, including sec...
John Heath, Marta Z. Kwiatkowska, Gethin Norman, D...
CSDA
2011
15 years 1 days ago
Approximate forward-backward algorithm for a switching linear Gaussian model
Motivated by the application of seismic inversion in the petroleum industry we consider a hidden Markov model with two hidden layers. The bottom layer is a Markov chain and given ...
Hugo Hammer, Håkon Tjelmeland