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» Flexible Priors for Exemplar-based Clustering
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UAI
2008
13 years 6 months ago
Flexible Priors for Exemplar-based Clustering
Exemplar-based clustering methods have been shown to produce state-of-the-art results on a number of synthetic and real-world clustering problems. They are appealing because they ...
Daniel Tarlow, Richard S. Zemel, Brendan J. Frey
NIPS
2007
13 years 6 months ago
DIFFRAC: a discriminative and flexible framework for clustering
We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
Francis Bach, Zaïd Harchaoui
ICML
2007
IEEE
14 years 6 months ago
The matrix stick-breaking process for flexible multi-task learning
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Ya Xue, David B. Dunson, Lawrence Carin
LWA
2004
13 years 6 months ago
Dirichlet Enhanced Latent Semantic Analysis
This paper describes nonparametric Bayesian treatments for analyzing records containing occurrences of items. The introduced model retains the strength of previous approaches that...
Kai Yu, Shipeng Yu, Volker Tresp
JMLR
2010
150views more  JMLR 2010»
13 years 5 days ago
Supervised Dimension Reduction Using Bayesian Mixture Modeling
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
Kai Mao, Feng Liang, Sayan Mukherjee