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ICML
2007
IEEE
16 years 7 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
TIP
2002
98views more  TIP 2002»
15 years 6 months ago
Joint-MAP Bayesian tomographic reconstruction with a gamma-mixture prior
We address the problem of Bayesian image reconstruction with a prior that captures the notion of a clustered intensity histogram. The problem is formulated in the framework of a j...
Ing-Tsung Hsiao, Anand Rangarajan, Gene Gindi
AAAI
2010
15 years 3 months ago
A Topic Model for Linked Documents and Update Rules for its Estimation
The latent topic model plays an important role in the unsupervised learning from a corpus, which provides a probabilistic interpretation of the corpus in terms of the latent topic...
Zhen Guo, Shenghuo Zhu, Zhongfei Zhang, Yun Chi, Y...
BMCBI
2010
178views more  BMCBI 2010»
15 years 6 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
CVPR
2004
IEEE
16 years 8 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong