1 code implementation • 15 Mar 2024 • Wanfang Su, Lixing Chen, Yang Bai, Xi Lin, Gaolei Li, Zhe Qu, Pan Zhou
The core philosophy of CMiMC is to preserve discriminative information of individual views in the collaborative view by maximizing mutual information between pre- and post-collaboration features while enhancing the efficacy of collaborative views by minimizing the loss function of downstream tasks.
no code implementations • CVPR 2023 • Zhe Qu, Xingyu Li, Xiao Han, Rui Duan, Chengchao Shen, Lixing Chen
Intuitively, these poor clients may come from biased universal information shared with others.
no code implementations • 11 Dec 2021 • Yang Bai, Lixing Chen, Shaolei Ren, Jie Xu
The core of our method is a DNN selection module that learns user QoE patterns on-the-fly and identifies the best-fit DNN for on-thing inference with the learned knowledge.
no code implementations • 2 Dec 2021 • Zhe Qu, Rui Duan, Lixing Chen, Jie Xu, Zhuo Lu, Yao Liu
In addition, client selection for HFL faces more challenges than conventional FL, e. g., the time-varying connection of client-ES pairs and the limited budget of the Network Operator (NO).
no code implementations • 2 Feb 2021 • Letian Zhang, Lixing Chen, Jie Xu
The basic idea of this system is to partition a deep neural network (DNN) into a front-end part running on the mobile device and a back-end part running on the edge server, with the key challenge being how to locate the optimal partition point to minimize the end-to-end inference delay.
no code implementations • 10 Jan 2021 • Jie Xu, Heqiang Wang, Lixing Chen
For cooperative FL service providers, we design a distributed bandwidth allocation algorithm to optimize the overall performance of multiple FL services, meanwhile cater to the fairness among FL services and the privacy of clients.
no code implementations • NeurIPS 2018 • Lixing Chen, Jie Xu, Zhuo Lu
In this paper, we study the stochastic contextual combinatorial multi-armed bandit (CC-MAB) framework that is tailored for volatile arms and submodular reward functions.
no code implementations • 7 Oct 2018 • Lixing Chen, Jie Xu, Shaolei Ren, Pan Zhou
To solve this problem and optimize the edge computing performance, we propose SEEN, a Spatial-temporal Edge sErvice placemeNt algorithm.
no code implementations • 17 Mar 2017 • Jie Xu, Lixing Chen, Shaolei Ren
Mobile edge computing (a. k. a.