Add to ORKGThis report presents probability inequalities for sums of adapted sequences of random, self-adjoint matrices. The results frame simple, easily verifiable hypotheses on the summands, and they yield strong conclusions about the large-deviation behavior of the maximum eigenvalue of the sum. The methods also specialize to sums of independent random matrices
Let N−−√+λmaxN+λmax be the largest real eigenvalue of a random N×NN×N matrix with independent N(0,1)...
This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm ...
This paper establishes new concentration inequalities for random matrices constructed from independe...
This report presents probability inequalities for sums of adapted sequences of random, self-adjoint...
This work presents probability inequalities for sums of independent, random, self-adjoint matrices....
In contemporary applied and computational mathematics, a frequent challenge is to bound the expectat...
Freedman's inequality is a martingale counterpart to Bernstein's inequality. This result shows that ...
This thesis contains a study of martingales. Some well-known results of probability theory are exte...
© 2016 Massachusetts Institute of Technology. The techniques of random matrices have played an impor...
This work introduces the minimax Laplace transform method, a modification of the cumulant-based matr...
This work prepares new probability bounds for sums of random, inde-pendent, Hermitian tensors. These...
We study the spectral norm of matrices $BA$, where $A$ is a random matrix with independent mean zero...
This paper considers a class of entropy functionals defined for random matrices, and it demonstrates...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
International audienceA sum rule relative to a reference measure on R is a relationship between the ...
Let N−−√+λmaxN+λmax be the largest real eigenvalue of a random N×NN×N matrix with independent N(0,1)...
This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm ...
This paper establishes new concentration inequalities for random matrices constructed from independe...
This report presents probability inequalities for sums of adapted sequences of random, self-adjoint...
This work presents probability inequalities for sums of independent, random, self-adjoint matrices....
In contemporary applied and computational mathematics, a frequent challenge is to bound the expectat...
Freedman's inequality is a martingale counterpart to Bernstein's inequality. This result shows that ...
This thesis contains a study of martingales. Some well-known results of probability theory are exte...
© 2016 Massachusetts Institute of Technology. The techniques of random matrices have played an impor...
This work introduces the minimax Laplace transform method, a modification of the cumulant-based matr...
This work prepares new probability bounds for sums of random, inde-pendent, Hermitian tensors. These...
We study the spectral norm of matrices $BA$, where $A$ is a random matrix with independent mean zero...
This paper considers a class of entropy functionals defined for random matrices, and it demonstrates...
This paper derives exponential concentration inequalities and polynomial moment inequalities for the...
International audienceA sum rule relative to a reference measure on R is a relationship between the ...
Let N−−√+λmaxN+λmax be the largest real eigenvalue of a random N×NN×N matrix with independent N(0,1)...
This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm ...
This paper establishes new concentration inequalities for random matrices constructed from independe...