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ICML
2007
IEEE
16 years 7 months ago
A dependence maximization view of clustering
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
Le Song, Alexander J. Smola, Arthur Gretton, Karst...
ICML
2007
IEEE
16 years 7 months ago
Local dependent components
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
Arto Klami, Samuel Kaski
ICML
2008
IEEE
16 years 7 months ago
Memory bounded inference in topic models
What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version...
Ryan Gomes, Max Welling, Pietro Perona
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
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ISBI
2009
IEEE
16 years 1 months ago
Probabilistic Branching Node Detection Using Hybrid Local Features
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques...
Haibin Ling, Michael Barnathan, Vasileios Megalooi...