Results 31 to 40 of about 223 (114)
Incentive Mechanism for Multi-Task Federated Learning Under Budget Constraints [PDF]
Federated Learning (FL) is a distributed machine-learning paradigm that achieves data-privacy protection, and its performance depends on the quality and scale of the data source.
GU Yonggen, LI Guoxiao, WU Xiaohong, TAO Jie, ZHANG Yanqiong
core +1 more source
Efficient secure federated learning aggregation framework based on homomorphic encryption [PDF]
, 2023 In order to solve the problems of data security and communication overhead in federated learning, an efficient and secure federated aggregation framework based on homomorphic encryption was proposed.In the process of federated learning, the privacy and ...
Shengxing YU, Zhong CHEN
core +1 more source
Intrusion detection method for IoT in heterogeneous environment [PDF]
In order to address the issue of inadequate training efficiency and subpar model performance encountered by Internet of things (IoT) devices when dealing with resource constraints and non-independent and identically distributed (Non-IID) data, a novel ...
LAI Yingxu, LIU Jing, MU Zelin
core +1 more source
大数据当前数字政府建设已进入深水区，政务大数据平台作为数据底座支撑各类政务信息化应用，其隐私数据的安全性和合规性一直被业界广泛关注。联邦学习是一类解决数据孤岛的重要方法，基于联邦学习的政务一体化大数据平台应用具有较高的研究价值。首先，介绍政务大数据平台及联邦学习应用现状；然后，分析政务大数据平台面临的隐私数据的采集、分类分级、共享三大管理挑战；接着，阐述基于联邦学习的推荐算法和隐私集合求交技术的解决方法；最后，对政务大数据平台隐私数据的未来应用进行了总结和展望。
吴坚平, 陈超超, 金加和, 吴春明
doaj +1 more source
Research on data asset circulation and trading scheme integrating blockchain and federated learning technologies [PDF]
As a key production factor, data assets are gradually evolving into a crucial engine driving China’s stable growth and economic transformation. However, the circulation and trading of data assets face multiple challenges, including issues related to data
MO Zijia, ZHAO Chen
core +1 more source
Federated Learning Optimization Method in Non-IID Scenarios [PDF]
Federated Learning(FL) can collaborate to train global models without compromising data privacy. Nonetheless, this collaborative training approach faces the challenge of Non-IID in the real world; slow model convergence and low accuracy.
Huawei SONG, Shengqi LI, Fangjie WAN, Yuping WEI
core +1 more source
Research on mobile edge computing and caching in massive wireless communication network [PDF]
, 2021 For the large-scale network mobile edge computing and caching technology of future 6G mobile communications, firstly, the architectures and principles of mobile edge computing and caching in large-scale wireless networks were introduced, and the ...
Chong ZHENG +3 more
core +1 more source
Wildlife Letters, Volume 2, Issue 1, Page 23-32, March 2024.Most students had low knowledge of biodiversity conservation, a result quite shocking given they were enrolled in wildlife management courses. On the other hand, they had favorable perception and attitude to biodiversity conservation. Furthermore, students in higher level had better perception and attitude than those in lower levels.
Omolola O. Ajayi +2 more
wiley +1 more source
Federated learning-based user access strategy and energy consumption optimization in cell-free massive MIMO network [PDF]
, 2023 To solve the problem that how users choose access points in cell-free massive multiple-input multiple-output (CF-mMIMO) network, a prioritized access strategy for poorer users based on channel coefficient ranking was proposed.First, users were evaluated ...
Chunyu PAN +5 more
core +1 more source
Evidence of policy learning in emergency declarations as communication tools in Australia
Disasters, Volume 48, Issue 1, January 2024.Emergency declarations are important legal tools for the state to protect itself and its citizens during times of crisis. Such declarations permit the exercise of extraordinary powers to address an emergency or disaster. They present an opportunity to explore policy learning in crises, through the ability to examine emergency declaration instruments ...
Ben Beccari
wiley +1 more source