no code implementations • 18 Aug 2021 • Pengfei Hou, Ying Jin, Yukang Chen
Differentiable architecture search (DARTS) marks a milestone in Neural Architecture Search (NAS), boasting simplicity and small search costs.
1 code implementation • CVPR 2021 • Xuanyang Zhang, Pengfei Hou, Xiangyu Zhang, Jian Sun
In this paper, we investigate a new variant of neural architecture search (NAS) paradigm -- searching with random labels (RLNAS).
no code implementations • 15 Dec 2020 • Pengfei Hou, Ying Jin
The bias causes the architecture parameters of non-learnable operations to surpass that of learnable operations.
no code implementations • 25 Sep 2019 • Shizheng Qin, Yichen Zhu, Pengfei Hou, Xiangyu Zhang, Wenqiang Zhang, Jian Sun
In this paper, we propose a learnable sampling module based on variational auto-encoder (VAE) for neural architecture search (NAS), named as VAENAS, which can be easily embedded into existing weight sharing NAS framework, e. g., one-shot approach and gradient-based approach, and significantly improve the performance of searching results.
no code implementations • 1 Feb 2018 • Jingchu Liu, Pengfei Hou, Lisen Mu, Yinan Yu, Chang Huang
Tactical driving decision making is crucial for autonomous driving systems and has attracted considerable interest in recent years.