28 citations · 85 across the 16 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.LG2019★ 1 cited
AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture
Tunhou Zhang, Hsin-Pai Cheng, Zhenwen Li +4
Resource is an important constraint when deploying Deep Neural Networks (DNNs) on mobile and edge devices. Existing works commonly adopt the cell-based search approach, which limit…
cs.LG2019★ 8 cited
SwiftNet: Using Graph Propagation as Meta-knowledge to Search Highly Representative Neural Architectures
Hsin-Pai Cheng, Tunhou Zhang, Yukun Yang +5
Designing neural architectures for edge devices is subject to constraints of accuracy, inference latency, and computational cost. Traditionally, researchers manually craft deep neu…
cs.LG2019★ 6 cited
AutoGrow: Automatic Layer Growing in Deep Convolutional Networks
Wei Wen, Feng Yan, Yiran Chen +1
Depth is a key component of Deep Neural Networks (DNNs), however, designing depth is heuristic and requires many human efforts. We propose AutoGrow to automate depth discovery in D…