LHOPT: A Generalizable Approach to Learning Optimizers

https://arxiv.org/abs/2106.00958 A Generalizable Approach to Learning Optimizers A core issue with learning to optimize neural networks has been the lack of generalization to real world problems. To address this, we describe a system designed from a generalization-first perspective, learning to update optimizer hyperparameters instead arxiv.org A core issue with learning to optimize neural netwo..

2021.06.06