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CVPR
2005
IEEE
14 years 11 months ago
Mixture Trees for Modeling and Fast Conditional Sampling with Applications in Vision and Graphics
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...
Frank Dellaert, Vivek Kwatra, Sang Min Oh
UAI
2008
13 years 10 months ago
Sampling First Order Logical Particles
Approximate inference in dynamic systems is the problem of estimating the state of the system given a sequence of actions and partial observations. High precision estimation is fu...
Hannaneh Hajishirzi, Eyal Amir
CAEPIA
2003
Springer
14 years 2 months ago
A Method to Adaptively Propagate the Set of Samples Used by Particle Filters
Abstract. In recent years, particle filters have emerged as a useful tool that enables the application of Bayesian reasoning to problems requiring dynamic state estimation. The ef...
Alvaro Soto
IWMM
2000
Springer
108views Hardware» more  IWMM 2000»
14 years 20 days ago
Efficient Object Sampling via Weak References
The performance of automatic memory management may be improved if the policies used in allocating and collecting objects had knowledge of the lifetimes of objects. To date, approa...
Ole Agesen, Alex Garthwaite
TNN
2008
177views more  TNN 2008»
13 years 9 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