no code implementations • 18 Mar 2024 • Zhuoyuan Li, Zikun Yuan, Li Li, Dong Liu, Xiaohu Tang, Feng Wu
Moreover, segmentation mask is considered in the joint rate-distortion optimization for motion estimation and partition estimation to derive the motion vector of different regions and partition more accurately.
no code implementations • 23 Aug 2023 • Ranggi Hwang, Jianyu Wei, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, Mao Yang
To tackle the high compute requirements of LLMs, the Mixture-of-Experts (MoE) architecture was introduced which is able to scale its model size without proportionally scaling up its computational requirements.
no code implementations • 21 Jun 2023 • Cheng Yang, Xue Yang, Dongxian Wu, Xiaohu Tang
Then the server aggregates all the proxy datasets to form a central dummy dataset, which is used to finetune aggregated global model.
no code implementations • 15 Jun 2023 • Xue Yang, Zifeng Liu, Xiaohu Tang, Rongxing Lu, Bo Liu
With the emergence of privacy leaks in federated learning, secure aggregation protocols that mainly adopt either homomorphic encryption or threshold secret sharing have been widely developed for federated learning to protect the privacy of the local training data of each client.
no code implementations • 30 May 2023 • Yanyan Wang, Qidi Li, Xiaohu Tang
Based on the three-dimensional (3D) received signal of the splitting receiver, we derive an equivalent two-dimensional (2D) signal model and develop a low-complexity signal detection method for the practical modulation scheme.
no code implementations • 7 Feb 2023 • Xiaohu Tang, Yang Wang, Ting Cao, Li Lyna Zhang, Qi Chen, Deng Cai, Yunxin Liu, Mao Yang
On-device Deep Neural Network (DNN) inference consumes significant computing resources and development efforts.
1 code implementation • 23 Feb 2020 • Xue Yang, Yan Feng, Weijun Fang, Jun Shao, Xiaohu Tang, Shu-Tao Xia, Rongxing Lu
However, the strong defence ability and high learning accuracy of these schemes cannot be ensured at the same time, which will impede the wide application of FL in practice (especially for medical or financial institutions that require both high accuracy and strong privacy guarantee).