过去一年中添加的文章，按日期排序
LOS/Multipath/NLOS Classifiers using Machine learning and Raytracing. A preliminary study to identify and address the Mulitpath error
K Upendra - 2024 - odr.chalmers.se
1 天前 - … supervised machine learning, wireless communication … ,’ which exhibits promis ing
distribution and metrics when … we utilize a deep neural network architecture with GRU units …
distribution and metrics when … we utilize a deep neural network architecture with GRU units …
Det(Com)2: Deterministic Communication and Computation Integration Toward AIGC Services
W Zhang, N Tang, D Yang, R Guo… - … Communications, 2024 - ieeexplore.ieee.org
4 天前 - … as distributed training, rapid deployment, and collaborative inference. Deep
reinforcement learning… To address these challenges, we propose a three-layer network …
reinforcement learning… To address these challenges, we propose a three-layer network …
Dynamic Laser Inter-Satellite Link Scheduling Based on Federated Reinforcement Learning: An Asynchronous Hierarchical Architecture
7 天前 - … distribution, and all the data flows entering the network are denoted by f. Besides
the data flows entering the network, the distribution … of the LEO satellite network. To calculate …
the data flows entering the network, the distribution … of the LEO satellite network. To calculate …
User Classification and Traffic Steering in O-RAN
R Ntassah, GM Dell'area… - … of the Communications …, 2024 - ieeexplore.ieee.org
9 天前 - … of AI/ML techniques in the architecture, as presented by … , we present a two-tier
machine learning (ML) model designed … our proposed method: to enhance UE distribution across …
machine learning (ML) model designed … our proposed method: to enhance UE distribution across …
Multi-Cell Cooperative Resource Allocation and Performance Evaluation for Roadside-Assisted Automated Driving
S Yang, X Zhu, Y Li, Q Yuan, L Li - World Electric Vehicle Journal, 2024 - mdpi.com
10 天前 - … , the advent of wireless communication technologies such as 5G … Thus, a distributed
reinforcement learning strategy … on the option-critic architecture named multi-agent option-…
reinforcement learning strategy … on the option-critic architecture named multi-agent option-…
Distributed Combinatorial Optimization of Downlink User Assignment in mmWave Cell-free Massive MIMO Using Graph Neural Networks
12 天前 - … solution for future wireless communications. However, its … , we propose an
unsupervised machine learning (ML) … In this work, we employ a dedicated architecture similar to …
unsupervised machine learning (ML) … In this work, we employ a dedicated architecture similar to …
Federated Learning using TensorFlow
R Patil, D Gupta, HL Gururaj - Federated Learning Techniques and …, 2024 - World Scientific
14 天前 - … deep learning (DL) architectures such as convolutional neural networks (CNNs) and
recurrent neural net… model sizes being hard to distribute over mobile devices, large training …
recurrent neural net… model sizes being hard to distribute over mobile devices, large training …
Non-Federated Multi-Task Split Learning for Heterogeneous Sources
Y Zheng, A Eryilmaz - arXiv preprint arXiv:2406.00150, 2024 - arxiv.org
21 天前 - … As such, this work aims to introduce a new architecture … to multi-task distributed
machine learning which we cannot list … Learning, Split Learning, Split Federated Learning, and …
machine learning which we cannot list … Learning, Split Learning, Split Federated Learning, and …
Proactive Caching With Distributed Deep Reinforcement Learning in 6 G Cloud-Edge Collaboration Computing
C Wu, Z Xu, X He, Q Lou, Y Xia… - … and Distributed Systems, 2024 - ieeexplore.ieee.org
24 天前 - … we focus on the distributed deep reinforcement learning (DRL)-based method for
proactive … such a complex scenario, a distributed learning architecture, ie, multi-agent learning …
proactive … such a complex scenario, a distributed learning architecture, ie, multi-agent learning …
[PDF][PDF] Cyber Security and Applications
H Setia, A Chhabra, SK Singh, S Kumar, S Sharma… - researchgate.net
26 天前 - … on anticipating and mitigating Distributed Denial of Service … machine learning
techniques for classification and predictive analytics with an accuracy of 99.59%. The architecture …
techniques for classification and predictive analytics with an accuracy of 99.59%. The architecture …