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» Controlling the Complexity of HMM Systems by Regularization
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NIPS
1998
13 years 5 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll
CSL
2004
Springer
13 years 4 months ago
Factor analysed hidden Markov models for speech recognition
Recently various techniques to improve the correlation model of feature vector elements in speech recognition systems have been proposed. Such techniques include semi-tied covaria...
Antti-Veikko I. Rosti, M. J. F. Gales
ISTA
2007
13 years 5 months ago
Knowledge-Oriented Approach to the Main Pipeline Complex Dispatching Control
: The article is devoted to the development of knowledge-oriented models that are able to increase the efficiency and quality of main pipeline complex (MPC) dispatching control. Th...
O. Ye. Fedorovich, A. V. Prokhorov, K. V. Golovan
ICC
2009
IEEE
121views Communications» more  ICC 2009»
13 years 2 months ago
Three Layered Hidden Markov Models for Binary Digital Wireless Channels
Abstract--Generative models are created to be used in the design and performance assessment of high layer wireless communication protocols and some error control strategies. Genera...
Omar S. Salih, Cheng-Xiang Wang, David I. Laurenso...
ISPEC
2007
Springer
13 years 10 months ago
Privacy-Preserving Credentials Upon Trusted Computing Augmented Servers
Credentials are an indispensable means for service access control in electronic commerce. However, regular credentials such as X.509 certificates and SPKI/SDSI certificates do no...
Yanjiang Yang, Robert H. Deng, Feng Bao