Efficient NAS via Parameter Sharing
This paper proposes a novel approach to Efficient Neural Architecture Search (NAS) using parameter sharing. The authors introduce a new search space and an efficient algorithm to explore it, aiming to reduce the computational cost of NAS.
Summary
- The paper introduces a parameter-sharing-based NAS approach.
- It proposes a new search space and an efficient algorithm.
- The method aims to reduce the computational cost of NAS.
Key Points
- Parameter Sharing: The proposed method uses parameter sharing to reduce the number of parameters in the search space.
- Efficient Search Space: A new search space is introduced, which is more efficient to explore.
- Algorithm: An efficient algorithm is proposed to explore the new search space.
Applications
- The proposed approach can be applied to various domains, such as computer vision, natural language processing, and speech recognition.
Further Reading
- For more information, you can visit our Neural Architecture Search page.
Image