1 code implementation • CVPR 2023 • Shun Lu, Yu Hu, Longxing Yang, Zihao Sun, Jilin Mei, Jianchao Tan, Chengru Song
Our method only requires negligible computation cost for optimizing the sampling distributions of path and data, but achieves lower gradient variance during supernet training and better generalization performance for the supernet, resulting in a more consistent NAS.
no code implementations • ICCV 2023 • Zihao Sun, Yu Sun, Longxing Yang, Shun Lu, Jilin Mei, Wenxiao Zhao, Yu Hu
Neural Architecture Search (NAS) aims to automatically find optimal neural network architectures in an efficient way.
1 code implementation • International Conference on Machine Learning 2022 • Zihao Sun, Yu Hu, Shun Lu, Longxing Yang, Jilin Mei, Yinhe Han, Xiaowei Li
We utilize the attention weights to represent the importance of the relevant operations for the micro search or the importance of the relevant blocks for the macro search.
no code implementations • NeurIPS 2021 • Shun Lu, Jixiang Li, Jianchao Tan, Sen yang, Ji Liu
Predictor-based Neural Architecture Search (NAS) continues to be an important topic because it aims to mitigate the time-consuming search procedure of traditional NAS methods.
Ranked #21 on Neural Architecture Search on CIFAR-10
1 code implementation • BMVC 2021 • Shun Lu, Yu Hu, Longxing Yang, Zihao Sun, Jilin Mei, Yiming Zeng, Xiaowei Li
Differentiable Neural Architecture Search (DARTS) recently attracts a lot of research attention because of its high efficiency.
Ranked #9 on Neural Architecture Search on CIFAR-100
1 code implementation • 18 Sep 2021 • Wentao Zhu, Tianlong Kong, Shun Lu, Jixiang Li, Dawei Zhang, Feng Deng, Xiaorui Wang, Sen yang, Ji Liu
Recently, x-vector has been a successful and popular approach for speaker verification, which employs a time delay neural network (TDNN) and statistics pooling to extract speaker characterizing embedding from variable-length utterances.
Ranked #1 on Speaker Verification on VoxCeleb1
1 code implementation • ICLR 2021 • Xiangxiang Chu, Xiaoxing Wang, Bo Zhang, Shun Lu, Xiaolin Wei, Junchi Yan
We call this approach DARTS-.
Ranked #20 on Neural Architecture Search on NAS-Bench-201, CIFAR-10
1 code implementation • ICCV 2023 • Xiangxiang Chu, Shun Lu, Xudong Li, Bo Zhang
However, current two-stage neural architecture search methods are mainly limited to single-path search spaces.