Just a weighted sum, like:
k = 0.2
err = k * err1 + (1 - k) * err2?
How do I determine a good weight_decay value? Is this based on the norm of the gradient updates of one compared to that of the other?
Actually, I’m realizing the weight_decay might not work because it will decay the weight for both losses, no?