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JMLR
2010
156views more  JMLR 2010»
12 years 11 months ago
Classification with Incomplete Data Using Dirichlet Process Priors
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
KDD
2007
ACM
237views Data Mining» more  KDD 2007»
14 years 5 months ago
Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior
Documents, such as those seen on Wikipedia and Folksonomy, have tended to be assigned with multiple topics as a meta-data. Therefore, it is more and more important to analyze a re...
Issei Sato, Hiroshi Nakagawa
AAAI
2010
13 years 6 months ago
Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
Ian Porteous, Arthur Asuncion, Max Welling
ISIPTA
2005
IEEE
161views Mathematics» more  ISIPTA 2005»
13 years 10 months ago
Decision making under incomplete data using the imprecise Dirichlet model
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
Lev V. Utkin, Thomas Augustin