5 citations · 8 across the 7 of their papers we have counts for
3 papers · 1 filter
GeNAS: Neural Architecture Search with Better Generalization
Joonhyun Jeong, Joonsang Yu, Geondo Park +2
Neural Architecture Search (NAS) aims to automatically excavate the optimal network architecture with superior test performance. Recent neural architecture search (NAS) approaches…
Pipe-BD: Pipelined Parallel Blockwise Distillation
Hongsun Jang, Jaewon Jung, Jaeyong Song +3
Training large deep neural network models is highly challenging due to their tremendous computational and memory requirements. Blockwise distillation provides one promising method…
Enabling Hard Constraints in Differentiable Neural Network and Accelerator Co-Exploration
Deokki Hong, Kanghyun Choi, Hye Yoon Lee +4
Co-exploration of an optimal neural architecture and its hardware accelerator is an approach of rising interest which addresses the computational cost problem, especially in low-pr…