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WSC
1998
14 years 11 months ago
Stopping Criterion for a Simulation-Based Optimization Method
We consider a new simulation-based optimization method called the Nested Partitions (NP) method. This method generates a Markov chain and solving the optimization problem is equiv...
Sigurdur Ólafsson, Leyuan Shi
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 2 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
BMCBI
2005
100views more  BMCBI 2005»
14 years 9 months ago
Evolutionary models for insertions and deletions in a probabilistic modeling framework
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
Elena Rivas
CVPR
1998
IEEE
15 years 12 months ago
Nonlinear PHMMs for the Interpretation of Parameterized Gesture
In previous work [14], we modify the hidden Markov model (HMM) framework to incorporate a global parametric variation in the output probabilities of the states of the HMM. Develop...
Andrew D. Wilson, Aaron F. Bobick
CORR
1999
Springer
59views Education» more  CORR 1999»
14 years 9 months ago
HMM Specialization with Selective Lexicalization
We present a technique which complements Hidden Markov Models by incorporating some lexicalized states representing syntactically uncommon words. 'Our approach examines the d...
Jin-Dong Kim, Sang-Zoo Lee, Hae-Chang Rim