CanChen [email protected]
Neural Predictor for Neural Architecture Search
- Motivation: Current NAS algorithms require lots of computing resources.
- Method: This paper proposes a novel GCN-based network performance predictor and have done extensive experiments on ImageNet or NAS101.
- Contribution: This paper is not novel but in my opinion, network performance predictor is the future trend in accelerating NAS.
TAPAS
- Motivation: Current network performance methods do not take dataset difficulty into consideration.
- Method: The paper proposes a network performance predictor that can adjust to dataset difficulty. Another important thing is that this paper trains the network layer by layer.
- Contribution: What I learnt is that we can use NN to model a dataset fitting difficulty.