1 code implementation • 28 Mar 2024 • Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Song Han
By squeezing deep learning models into billions of IoT devices and microcontrollers (MCUs), we expand the scope of AI applications and enable ubiquitous intelligence.
no code implementations • 26 Oct 2023 • Ligeng Zhu, Lanxiang Hu, Ji Lin, Wei-Chen Wang, Wei-Ming Chen, Chuang Gan, Song Han
On-device learning and efficient fine-tuning enable continuous and privacy-preserving customization (e. g., locally fine-tuning large language models on personalized data).
5 code implementations • 1 Jun 2023 • Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, Song Han
We then propose to search for the optimal per-channel scaling that protects the salient weights by observing the activation, not weights.
2 code implementations • 8 Oct 2022 • Wei-Chen Wang, Jonas Mueller
Mislabeled examples are a common issue in real-world data, particularly for tasks like token classification where many labels must be chosen on a fine-grained basis.
1 code implementation • 30 Jun 2022 • Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han
To reduce the memory footprint, we propose Sparse Update to skip the gradient computation of less important layers and sub-tensors.