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» Finite State Transducers Approximating Hidden Markov Models
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ACL
1997
13 years 6 months ago
Finite State Transducers Approximating Hidden Markov Models
This paper describes the conversion of a Hidden Markov Model into a sequential transducer that closely approximates the behavior of the stochastic model. This transformation is es...
André Kempe
ECML
2006
Springer
13 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...
TCIAIG
2010
12 years 11 months ago
The Parametrized Probabilistic Finite-State Transducer Probe Game Player Fingerprint Model
Abstract--Fingerprinting operators generate functional signatures of game players and are useful for their automated analysis independent of representation or encoding. The theory ...
Jeffrey Tsang
CORR
2010
Springer
122views Education» more  CORR 2010»
12 years 12 months ago
Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR
We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavio...
Guangyue Han, Brian H. Marcus
ECML
2005
Springer
13 years 10 months ago
Inducing Hidden Markov Models to Model Long-Term Dependencies
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
Jérôme Callut, Pierre Dupont