Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Ghanavi, Rozhina"'
Publikováno v:
2021 IEEE Global Communications Conference (GLOBECOM)
Large datasets in machine learning often contain missing data, which necessitates the imputation of missing data values. In this work, we are motivated by network traffic classification, where traditional data imputation methods do not perform well.
Externí odkaz:
http://arxiv.org/abs/2303.10681
In this paper, we use an aerial base station (aerial-BS) to enhance fairness in a dynamic environment with user mobility. The problem of optimally placing the aerial-BS is a non-deterministic polynomial-time hard (NP-hard) problem. Moreover, the netw
Externí odkaz:
http://arxiv.org/abs/1909.08093
Autor:
Ghanavi, Rozhina, Kalantari, Elham, Sabbaghian, Maryam, Yanikomeroglu, Halim, Yongacoglu, Abbas
This paper considers an aerial base station (aerial-BS) assisted terrestrial network where user mobility is taken into account. User movement changes the network dynamically which may result in performance loss. To avoid this loss, guarantee a minimu
Externí odkaz:
http://arxiv.org/abs/1801.07472
Publikováno v:
International Journal of Mycobacteriology; 2021Supplement, Vol. 10, p75-75, 1p