no code implementations • 30 Sep 2024 • Ji Liu, Jiaxiang Ren, Ruoming Jin, Zijie Zhang, Yang Zhou, Patrick Valduriez, Dejing Dou
First, we propose a fisher information-based method to adaptively sample data within each device to improve the effectiveness of the FL fine-tuning process.
no code implementations • 26 Apr 2024 • Zhenghong Li, Jiaxiang Ren, Wensheng Cheng, Congwu Du, Yingtian Pan, Haibin Ling
Optical Doppler Tomography (ODT) is a blood flow imaging technique popularly used in bioengineering applications.
1 code implementation • 23 Oct 2023 • Tianshi Che, Ji Liu, Yang Zhou, Jiaxiang Ren, Jiwen Zhou, Victor S. Sheng, Huaiyu Dai, Dejing Dou
This paper proposes a Parameter-efficient prompt Tuning approach with Adaptive Optimization, i. e., FedPepTAO, to enable efficient and effective FL of LLMs.
no code implementations • 14 Jul 2022 • Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou
The federated learning (FL) framework enables edge clients to collaboratively learn a shared inference model while keeping privacy of training data on clients.
no code implementations • CVPR 2022 • Jiaxiang Ren, Kicheon Park, Yingtian Pan, Haibin Ling
With the structural information and appearance feature from noisy image as references, our model can remove larger BMA and produce better visualizing result.
no code implementations • NeurIPS 2021 • Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou
Despite achieving remarkable efficiency, traditional network pruning techniques often follow manually-crafted heuristics to generate pruned sparse networks.
no code implementations • 19 Oct 2021 • Heng Fan, Jiaxiang Ren, Jie Yang, Yi-Xian Qin, Haibin Ling
The aim of this study was to investigate whether a deep convolutional neural network (CNN) with an attention module can detect osteoporosis on panoramic radiographs.