You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization

Understand

Recently Neural Architecture Search (NAS) has aroused great interest in both academia and industry, however it remains challenging because of its huge and non-continuous search space.

• Instead of applying evolutionary algorithm or reinforcement learning as previous works, this paper proposes a Direct Sparse Optimization NAS (DSO-NAS) method.
• In DSO-NAS, we provide a novel model pruning view to NAS problem.
• In specific, we start from a completely connected block, and then introduce scaling factors to scale the information flow between operations.