Journal
ELECTRONIC COMMUNICATIONS IN PROBABILITY
Volume 18, Issue -, Pages 1-9Publisher
UNIV WASHINGTON, DEPT MATHEMATICS
DOI: 10.1214/ECP.v18-2865
Keywords
subgaussian random variables; concentration inequalities; random matrices
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Funding
- NSF [DMS 1161372, DMS 1001829, 1265782]
- Direct For Mathematical & Physical Scien [1161372] Funding Source: National Science Foundation
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [1265782, 1001829] Funding Source: National Science Foundation
- Division Of Mathematical Sciences [1161372] Funding Source: National Science Foundation
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In this expository note, we give a modern proof of Hanson-Wright inequality for quadratic forms in sub-gaussian random variables. We deduce a useful concentration inequality for sub-gaussian random vectors. Two examples are given to illustrate these results: a concentration of distances between random vectors and subspaces, and a bound on the norms of products of random and deterministic matrices.
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