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WSC
1998
15 years 2 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 5 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»
15 years 1 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
16 years 3 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
101
Voted
CORR
1999
Springer
59views Education» more  CORR 1999»
15 years 1 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