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Learning mixtures of arbitrary gaussians
S. Arora
, R. Kannan
Computer Science
Bendheim Center for Finance
Center for Statistics & Machine Learning
Princeton Language and Intelligence (PLI)
Research output
:
Contribution to journal
›
Conference article
›
peer-review
150
Scopus citations
Overview
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Keyphrases
Arbitrary Shape
100%
EM Algorithm
100%
Gaussian Mixture
100%
High Probability
100%
Lairds
100%
Local Search Heuristic
100%
Non-degeneracy Conditions
100%
Normal Mixture
100%
Number of Components
100%
Computer Science
Application Area
50%
Arbitrary Shape
50%
Gaussian Component
100%
Normal Distribution
50%
Search Heuristic
50%