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» Estimating Likelihoods for Topic Models
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PAMI
2010
132views more  PAMI 2010»
14 years 10 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel
ICML
2006
IEEE
16 years 16 days ago
Pachinko allocation: DAG-structured mixture models of topic correlations
Latent Dirichlet allocation (LDA) and other related topic models are increasingly popular tools for summarization and manifold discovery in discrete data. However, LDA does not ca...
Wei Li, Andrew McCallum
ICASSP
2008
IEEE
15 years 6 months ago
Weighted maximum likelihood autoregressive and moving average spectrum modeling
We propose new algorithms for estimating autoregressive (AR), moving average (MA), and ARMA models in the spectral domain. These algorithms are derived from a maximum likelihood a...
Roland Badeau, Bertrand David
JMLR
2008
141views more  JMLR 2008»
14 years 11 months ago
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models
In graphical modelling, a bi-directed graph encodes marginal independences among random variables that are identified with the vertices of the graph. We show how to transform a bi...
Mathias Drton, Thomas S. Richardson
VALUETOOLS
2006
ACM
15 years 5 months ago
Splitting with weight windows to control the likelihood ratio in importance sampling
Importance sampling (IS) is the most widely used efficiency improvement method for rare-event simulation. When estimating the probability of a rare event, the IS estimator is the ...
Pierre L'Ecuyer, Bruno Tuffin