This paper establishes new concentration inequalities for random matrices constructed from independent random variables. These results are analogous with the generalized Efron–Stein inequalities developed by Boucheron et al. The proofs rely on the method of exchangeable pairs
This monograph offers an invitation to the field of matrix concentration inequalities. It begins wit...
Random matrices now play a role in many areas of theoretical, applied, and computational mathematics...
Matrix concentration inequalities provide information about the probability that a random matrix is ...
This paper establishes new concentration inequalities for random matrices constructed from independe...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm ...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
Abstract: This paper derives exponential tail bounds and polynomial moment inequali-ties for the spe...
AbstractWe show that the mixing times of random walks on compact groups can be used to obtain concen...
This paper considers a class of entropy functionals defined for random matrices, and it demonstrates...
Matrix concentration inequalities give bounds for the spectral-norm deviation of a random matrix fro...
The Chernoff bound proves concentration for sums of independent Bernoulli random variables. As we ha...
2014-06-16Stein's method is a technique in probability theory introduced by Charles Stein in 1972 th...
This paper develops nonasymptotic growth and concentration bounds for a product of independent rando...
This monograph offers an invitation to the field of matrix concentration inequalities. It begins wit...
Random matrices now play a role in many areas of theoretical, applied, and computational mathematics...
Matrix concentration inequalities provide information about the probability that a random matrix is ...
This paper establishes new concentration inequalities for random matrices constructed from independe...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm ...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
Abstract: This paper derives exponential tail bounds and polynomial moment inequali-ties for the spe...
AbstractWe show that the mixing times of random walks on compact groups can be used to obtain concen...
This paper considers a class of entropy functionals defined for random matrices, and it demonstrates...
Matrix concentration inequalities give bounds for the spectral-norm deviation of a random matrix fro...
The Chernoff bound proves concentration for sums of independent Bernoulli random variables. As we ha...
2014-06-16Stein's method is a technique in probability theory introduced by Charles Stein in 1972 th...
This paper develops nonasymptotic growth and concentration bounds for a product of independent rando...
This monograph offers an invitation to the field of matrix concentration inequalities. It begins wit...
Random matrices now play a role in many areas of theoretical, applied, and computational mathematics...
Matrix concentration inequalities provide information about the probability that a random matrix is ...
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