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ICML
2008
IEEE
16 years 7 months ago
The dynamic hierarchical Dirichlet process
The dynamic hierarchical Dirichlet process (dHDP) is developed to model the timeevolving statistical properties of sequential data sets. The data collected at any time point are r...
Lu Ren, David B. Dunson, Lawrence Carin
ICML
2004
IEEE
16 years 7 months ago
Learning Bayesian network classifiers by maximizing conditional likelihood
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Daniel Grossman, Pedro Domingos
ISBI
2002
IEEE
16 years 7 months ago
Statistically-based reorientation of diffusion tensor field
This paper presents a new method for warping of diffusion tensor fields. The proper reorientation of a tensor field requires knowledge of the underlying fiber orientation, which i...
Dongrong Xu, Susumu Mori, Dinggang Shen, Christos ...
ISBI
2008
IEEE
16 years 7 months ago
Learning non-homogenous textures and the unlearning problem with application to drusen detection in retinal images
In this work we present a novel approach for learning nonhomogenous textures without facing the unlearning problem. Our learning method mimics the human behavior of selective lear...
Noah Lee, Andrew F. Laine, Theodore R. Smith
ICFP
2009
ACM
16 years 7 months ago
Purely functional lazy non-deterministic programming
Functional logic programming and probabilistic programming have demonstrated the broad benefits of combining laziness (non-strict evaluation with sharing of the results) with non-...
Sebastian Fischer, Oleg Kiselyov, Chung-chieh Shan