Machine Learning, Artificial Intelligence, Meta Learning.
this work starts with random initialization. A less explored approach is plastic networks which change with respect to their timesteps. We use RNN’s to store activation patterns or evolving forms of local Hebbian Learning rules. Early work tried to find the parameter to a parameterized learning