Learning to Mutate with Hypergradient Guided Population

NIPS 2020, 2020.

Cited by: 0|Views27
EI
Weibo:
We show the hyperparameter and mutation schedule learned by hyperparameter mutation in Fig. 5b and Fig. 5c

Abstract:

Computing the gradient of model hyperparameters, i.e., hypergradient, enables a promising and natural way to solve the hyperparameter optimization task. However, gradient-based methods could lead to suboptimal solutions due to the non-convex nature of optimization in a complex hyperparameter space. In this study, we propose a hyperparamet...More

Code:

Data:

0
Your rating :
0

 

Tags
Comments