  We study a high-dimensional generalized linear model and penalized empirical
risk minimization with $\ell_1$ penalty. Our aim is to provide a non-trivial
illustration that non-asymptotic bounds for the estimator can be obtained
without relying on the chaining technique and/or the peeling device.
