Training Models with PyTorch
Download in pdf format We consider a learning problem with input observations $\bbx\in\reals^n$ and output information $\bby\in\reals^m$. We use a linear learning parametrization that we want to train to predict outputs as $\hby=\bbH\bbx$ that are close to the real $\bby$. The comparison metric between $\bby$ and $\hby$ is the squared Euclidean error $\ell(\bby, \hby) = … Read more