Interblock Flow Prediction With Relation Graph Network for Cold Start on Bike-Sharing System
As the IoT technology becomes well established and sharing economy expands worldwide,
the bike-sharing system (BSS) has spread fast in the last decade. When introducing the BSS …
the bike-sharing system (BSS) has spread fast in the last decade. When introducing the BSS …
Adds: Adaptive differentiable sampling for robust multi-party learning
Distributed multi-party learning provides an effective approach for training a joint model with
scattered data under legal and practical constraints. However, due to the quagmire of a …
scattered data under legal and practical constraints. However, due to the quagmire of a …
FLSwitch: Towards Secure and Fast Model Aggregation for Federated Deep Learning with a Learning State-Aware Switch
Security and efficiency are two desirable properties of federated learning (FL). To enforce
data security for FL participants, homomorphic encryption (HE) is widely adopted. However …
data security for FL participants, homomorphic encryption (HE) is widely adopted. However …
Communication-efficient federated learning with an event-triggering strategy
Y Li, J Bai, D Li, W Li - 2022 IEEE 11th Data Driven Control and …, 2022 - ieeexplore.ieee.org
With the development of artificial intelligence, data has become one of the most important
resources. However, the emphasis on data privacy has brought great obstacles to the further …
resources. However, the emphasis on data privacy has brought great obstacles to the further …
Adaptive lazily aggregation based on error accumulation
X Chen, G Liu - 2023 4th International Conference on Electronic …, 2023 - ieeexplore.ieee.org
Federated Learning (FL) enables multiple clients to collaboratively train models without
exposing their local data. FL is an effective approach to utilizing localized data while …
exposing their local data. FL is an effective approach to utilizing localized data while …
Research on efficient federated learning communication mechanism based on adaptive gradient compression
L TANG, Z WANG, H PU, Z WU, Q CHEN - 电子与信息学报, 2023 - jeit.ac.cn
Considering the non-negligible communication cost problem caused by redundant gradient
interactive communication between a large number of device nodes in the Federated …
interactive communication between a large number of device nodes in the Federated …
MMSE Threshold-based Power Control for Wireless Federated Learning
YS Hsu, RH Gau - 2023 IEEE 97th Vehicular Technology …, 2023 - ieeexplore.ieee.org
We put forward a novel minimum mean square error (MMSE) threshold-based power control
scheme for wireless federated learning in digital communication systems. The proposed …
scheme for wireless federated learning in digital communication systems. The proposed …
Privacy-Preserving and Models Intrusion Detection Federated Deep Learning Challenges, Schemas and Future Trajectories
Y Yu, L Jianping, D Weiwei - 2022 19th International Computer …, 2022 - ieeexplore.ieee.org
Deep learning has made remarkable research advancements and wide-ranging
applications in the domains of computer vision, multimodal, natural language processing …
applications in the domains of computer vision, multimodal, natural language processing …
A Momentum-Based Wireless Federated Learning Acceleration With Distributed Principle Decomposition
In the uplink period of wireless federated learning (WFL), multiple workers frequently upload
uncoded training information to a server via orthogonal wireless channels. Due to the …
uncoded training information to a server via orthogonal wireless channels. Due to the …
A Unified Framework for Understanding Distributed Optimization Algorithms: System Design and its Applications
X Zhang - 2023 - search.proquest.com
More than ever before, technology advances across the spectrum have meant that we have
individualized and decentralized access to data, resources, and human capital. The …
individualized and decentralized access to data, resources, and human capital. The …