[D] Learning one representation for multiple tasks – favoring some tasks over others?
Are there any papers on balancing the impact of multiple tasks on the final single representation?
Let there be n tasks to be solved by one representation:
L_total = L_t1 + L_t2 + … + L_tn
If we want to favor one task over another based on prior knowledge is there any other way than setting a lambda type hyperparameter to increase the loss for a specific task?