  We introduce a Bernstein-type inequality which serves to uniformly control
quadratic forms of gaussian variables. The latter can for example be used to
derive sharp model selection criteria for linear estimation in linear
regression and linear inverse problems via penalization, and we do not exclude
that its scope of application can be made even broader.
