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ER
2007
Springer
193views Database» more  ER 2007»
16 years 1 months ago
Applying Model Transformation By-Example on Business Process Modeling Languages
Model transformations are playing a vital role in the field of model engineering. However, for non-trivial transformation issues most approaches require imperative definitions, w...
Michael Strommer, Marion Murzek, Manuel Wimmer
ICML
1999
IEEE
16 years 7 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
ICMI
2010
Springer
220views Biometrics» more  ICMI 2010»
15 years 4 months ago
Visual speech synthesis by modelling coarticulation dynamics using a non-parametric switching state-space model
We present a novel approach to speech-driven facial animation using a non-parametric switching state space model based on Gaussian processes. The model is an extension of the shar...
Salil Deena, Shaobo Hou, Aphrodite Galata
VLDB
2008
ACM
196views Database» more  VLDB 2008»
16 years 7 months ago
Modelling retrieval models in a probabilistic relational algebra with a new operator: the relational Bayes
This paper presents a probabilistic relational modelling (implementation) of the major probabilistic retrieval models. Such a high-level implementation is useful since it supports ...
Thomas Rölleke, Hengzhi Wu, Jun Wang, Hany Azzam
KDD
2008
ACM
115views Data Mining» more  KDD 2008»
16 years 7 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...