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Testing for high-dimensional geometry in random graphs
Sébastien Bubeck
, Jian Ding
, Ronen Eldan
, Miklós Z. Rácz
Operations Research & Financial Engineering
Center for Statistics & Machine Learning
Research output
:
Contribution to journal
›
Article
›
peer-review
101
Scopus citations
Overview
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Dive into the research topics of 'Testing for high-dimensional geometry in random graphs'. Together they form a unique fingerprint.
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Mathematics
Random Graph
100%
Matrix (Mathematics)
66%
Triangle
33%
Concludes
33%
Total Variation Distance
33%
Geometric Structure
33%
Testing Procedure
33%
Random Vector
33%
Keyphrases
Independent Random Vectors
33%
Sparse Regime
33%
Latent Vector
33%
Signed Triangle
33%
Detection Boundary
33%