no code implementations • 8 Jul 2020 • Hsin-Pai Cheng, Tunhou Zhang, Yixing Zhang, Shi-Yu Li, Feng Liang, Feng Yan, Meng Li, Vikas Chandra, Hai Li, Yiran Chen
To preserve graph correlation information in encoding, we propose NASGEM which stands for Neural Architecture Search via Graph Embedding Method.
1 code implementation • ICML 2020 • Shi-Yu Li, Edward Hanson, Hai Li, Yiran Chen
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 these SOTA CNNs onto resource-constrained devices.
no code implementations • 1 Jul 2019 • Shi-Yu Li, Yun-Long Li, Tong-Jie Zhang
This work uses a combination of a variational auto-encoder and generative adversarial network to compare different dark energy models in light of observations, e. g., the distance modulus from type Ia supernovae.
1 code implementation • 19 Jun 2019 • Hsin-Pai Cheng, Tunhou Zhang, Yukun Yang, Feng Yan, Shi-Yu Li, Harris Teague, Hai Li, Yiran Chen
Designing neural architectures for edge devices is subject to constraints of accuracy, inference latency, and computational cost.
no code implementations • 27 Nov 2018 • Hsin-Pai Cheng, Patrick Yu, Haojing Hu, Feng Yan, Shi-Yu Li, Hai Li, Yiran Chen
Distributed learning systems have enabled training large-scale models over large amount of data in significantly shorter time.