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This paper investigates deep learning enabled beamforming design for ultra-dense wireless networks by integrating prior knowledge and graph neural network (GNN), named model-based GNN. A energy efficiency (EE) maximization problem is formulated subje
Externí odkaz:
http://arxiv.org/abs/2410.02289
This paper applies graph neural networks (GNN) in UAV communications to optimize the placement and transmission design. We consider a multiple-user multiple-input-single-output UAV communication system where a UAV intends to find a placement to hover
Externí odkaz:
http://arxiv.org/abs/2410.02277
Machine learning (ML) models are powerful tools for detecting complex patterns within data, yet their "black box" nature limits their interpretability, hindering their use in critical domains like healthcare and finance. To address this challenge, in
Externí odkaz:
http://arxiv.org/abs/2408.17016
Autor:
Lu, Yang, Zhan, Felix
This study evaluates the applicability of Kolmogorov-Arnold Networks (KAN) in fraud detection, finding that their effectiveness is context-dependent. We propose a quick decision rule using Principal Component Analysis (PCA) to assess the suitability
Externí odkaz:
http://arxiv.org/abs/2408.10263
Personalized Federated Learning (PFL) aims to acquire customized models for each client without disclosing raw data by leveraging the collective knowledge of distributed clients. However, the data collected in real-world scenarios is likely to follow
Externí odkaz:
http://arxiv.org/abs/2408.02019
Autor:
MCDERMOTT, EMILY
Publikováno v:
Flash Art International; Summer2024, Vol. 57 Issue 347, p114-127, 14p
Mechanical amorphization, a widely observed phenomenon, has been utilized to synthesize novel phases by inducing disorder through external loading, thereby expanding the realm of glass-forming systems. Empirically, it has been plausible that mechanic
Externí odkaz:
http://arxiv.org/abs/2406.15722
Autor:
Lu, Yang, Yao, Weijia, Xiao, Yongqian, Zhang, Xinglong, Xu, Xin, Wang, Yaonan, Xiao, Dingbang
In obstacle-dense scenarios, providing safe guidance for mobile robots is critical to improve the safe maneuvering capability. However, the guidance provided by standard guiding vector fields (GVFs) may limit the motion capability due to the improper
Externí odkaz:
http://arxiv.org/abs/2405.08283
Autor:
Yin, Xiangbo, Shi, Jiangming, Zhang, Yachao, Lu, Yang, Zhang, Zhizhong, Xie, Yuan, Qu, Yanyun
Unsupervised Visible-Infrared Person Re-identification (USVI-ReID) presents a formidable challenge, which aims to match pedestrian images across visible and infrared modalities without any annotations. Recently, clustered pseudo-label methods have be
Externí odkaz:
http://arxiv.org/abs/2405.05613