10 citations · 26 across the 3 of their papers we have counts for
4 papers
NASGEM: Neural Architecture Search via Graph Embedding Method
Hsin-Pai Cheng, Tunhou Zhang, Yixing Zhang +7
Neural Architecture Search (NAS) automates and prospers the design of neural networks. Estimator-based NAS has been proposed recently to model the relationship between architecture…
PENNI: Pruned Kernel Sharing for Efficient CNN Inference
Shiyu Li, Edward Hanson, Hai Li +1
Although state-of-the-art (SOTA) CNNs achieve outstanding performance on various tasks, their high computation demand and massive number of parameters make it difficult to deploy t…
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…
LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning
Hsin-Pai Cheng, Patrick Yu, Haojing Hu +4
Distributed learning systems have enabled training large-scale models over large amount of data in significantly shorter time. In this paper, we focus on decentralized distributed…