In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to popularity of compressed sensing (CS) based reconstructions. One problem CS approaches is determining regularization parameters, control balance between fidelity and regularization. We propose a data-driven approach ...