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JMLR
2010
137views more  JMLR 2010»
13 years 2 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
WSC
2007
13 years 9 months ago
Path-sampling for state-dependent importance sampling
State-dependent importance sampling (SDIS) has proved to be particularly useful in simulation (specially in rare event analysis of stochastic systems). One approach for designing ...
Jose H. Blanchet, Jingchen Liu
WSC
2004
13 years 8 months ago
An Importance Sampling Method for Portfolios of Credit Risky Assets
The distribution of possible future losses for a portfolio of credit risky corporate assets, such as bonds or loans, shows strongly asymmetric behavior and a fat tail as the conse...
William J. Morokoff
TNN
2008
177views more  TNN 2008»
13 years 7 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
QUESTA
2007
95views more  QUESTA 2007»
13 years 7 months ago
Alternative proof and interpretations for a recent state-dependent importance sampling scheme
Recently, a state-dependent change of measure for simulating overflows in the two-node tandem queue was proposed by Dupuis et al. (Ann. Appl. Probab. 17(4):1306– 1346, 2007), to...
Pieter-Tjerk de Boer, Werner R. W. Scheinhardt