1241 search results - page 34 / 249 » Robust Bayesian clustering |
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
NIPS
2004
13 years 9 months ago
2004
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
CSDA
2008
13 years 7 months ago
2008
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
IJCAI
2007
13 years 9 months ago
2007
Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
CLUSTER
2007
IEEE
14 years 2 months ago
2007
IEEE
— A schedule is said robust if it is able to absorb some degree of uncertainty in tasks duration while maintaining a stable solution. This intuitive notion of robustness has led ...