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» Learning Mixtures of DAG Models
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165
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NIPS
2000
15 years 5 months ago
On Reversing Jensen's Inequality
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
Tony Jebara, Alex Pentland
124
Voted
JMLR
2008
83views more  JMLR 2008»
15 years 3 months ago
Generalization from Observed to Unobserved Features by Clustering
We argue that when objects are characterized by many attributes, clustering them on the basis of a random subset of these attributes can capture information on the unobserved attr...
Eyal Krupka, Naftali Tishby
ECCV
2002
Springer
16 years 5 months ago
Robust Parameterized Component Analysis
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Fernando De la Torre, Michael J. Black
139
Voted
ICPR
2008
IEEE
16 years 4 months ago
A novel Gaussianized vector representation for natural scene categorization
This paper presents a novel Gaussianized vector representation for scene images by an unsupervised approach. First, each image is encoded as an ensemble of orderless bag of featur...
Hao Tang, Mark Hasegawa-Johnson, Thomas S. Huang, ...
196
Voted
AII
1992
15 years 7 months ago
Learning from Multiple Sources of Inaccurate Data
Most theoretical models of inductive inference make the idealized assumption that the data available to a learner is from a single and accurate source. The subject of inaccuracies ...
Ganesh Baliga, Sanjay Jain, Arun Sharma