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.
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 • 15 Dec 2020 • Pengfei Hou, Ying Jin
The bias causes the architecture parameters of non-learnable operations to surpass that of learnable operations.
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 • 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.