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ICML
2005
IEEE
14 years 6 months ago
Predictive low-rank decomposition for kernel methods
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
Francis R. Bach, Michael I. Jordan
CIVR
2008
Springer
125views Image Analysis» more  CIVR 2008»
13 years 7 months ago
Leveraging user query log: toward improving image data clustering
Image clustering is useful in many retrieval and classification applications. The main goal of image clustering is to partition a given dataset into salient clusters such that the...
Hao Cheng, Kien A. Hua, Khanh Vu
SGP
2007
13 years 7 months ago
Surface reconstruction using local shape priors
We present an example-based surface reconstruction method for scanned point sets. Our approach uses a database of local shape priors built from a set of given context models that ...
Ran Gal, Ariel Shamir, Tal Hassner, Mark Pauly, Da...
PRL
2010
158views more  PRL 2010»
13 years 3 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
BMCBI
2004
146views more  BMCBI 2004»
13 years 5 months ago
Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data
Background: Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have...
Feng Gao, Barrett C. Foat, Harmen J. Bussemaker