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JMLR
2010
175views more  JMLR 2010»
13 years 4 months ago
Hierarchical Convex NMF for Clustering Massive Data
We present an extension of convex-hull non-negative matrix factorization (CH-NMF) which was recently proposed as a large scale variant of convex non-negative matrix factorization ...
Kristian Kersting, Mirwaes Wahabzada, Christian Th...
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 10 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICIP
1997
IEEE
14 years 11 months ago
An Optimization Approach to Unsupervised Hierarchical Texture Segmentation
In this paper we introduce a novel optimization framework for hierarchical data clustering and apply it to the problem of unsupervised texture segmentation. The proposed objective...
Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
ICML
2007
IEEE
14 years 11 months ago
Hierarchical Gaussian process latent variable models
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Neil D. Lawrence, Andrew J. Moore
ICML
2005
IEEE
14 years 11 months ago
A causal approach to hierarchical decomposition of factored MDPs
We present Variable Influence Structure Analysis, an algorithm that dynamically performs hierarchical decomposition of factored Markov decision processes. Our algorithm determines...
Anders Jonsson, Andrew G. Barto