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CVPR
2008
IEEE
14 years 5 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
ICML
2009
IEEE
14 years 4 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani

Publication
252views
13 years 6 months ago
Context models on sequences of covers
We present a class of models that, via a simple construction, enables exact, incremental, non-parametric, polynomial-time, Bayesian inference of conditional measures. The approac...
Christos Dimitrakakis
ACL
2012
11 years 6 months ago
A Nonparametric Bayesian Approach to Acoustic Model Discovery
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
Chia-ying Lee, James R. Glass
AAAI
2010
13 years 5 months ago
A Bayesian Nonparametric Approach to Modeling Mobility Patterns
Constructing models of mobile agents can be difficult without domain-specific knowledge. Parametric models flexible enough to capture all mobility patterns that an expert believes...
Joshua Mason Joseph, Finale Doshi-Velez, Nicholas ...