Zobrazeno 1 - 10
of 225
pro vyhledávání: '"Yılmaz, Selim"'
We consider collaborative inference at the wireless edge, where each client's model is trained independently on their local datasets. Clients are queried in parallel to make an accurate decision collaboratively. In addition to maximizing the inferenc
Externí odkaz:
http://arxiv.org/abs/2407.21151
We consider low-latency image transmission over a noisy wireless channel when correlated side information is present only at the receiver side (the Wyner-Ziv scenario). In particular, we are interested in developing practical schemes using a data-dri
Externí odkaz:
http://arxiv.org/abs/2310.04311
We consider the image transmission problem over a noisy wireless channel via deep learning-based joint source-channel coding (DeepJSCC) along with a denoising diffusion probabilistic model (DDPM) at the receiver. Specifically, we are interested in th
Externí odkaz:
http://arxiv.org/abs/2309.15889
Autor:
Perifanis, Vasileios, Pavlidis, Nikolaos, Yilmaz, Selim F., Wilhelmi, Francesc, Guerra, Elia, Miozzo, Marco, Efraimidis, Pavlos S., Dini, Paolo, Koutsiamanis, Remous-Aris
Cellular traffic prediction is a crucial activity for optimizing networks in fifth-generation (5G) networks and beyond, as accurate forecasting is essential for intelligent network design, resource allocation and anomaly mitigation. Although machine
Externí odkaz:
http://arxiv.org/abs/2309.10645
Intrusion detection is an indispensable part of RPL security due to its nature opening to attacks from insider attackers. While there are a good deal of studies that analyze different types of attack and propose intrusion detection systems based on v
Externí odkaz:
http://arxiv.org/abs/2303.16561
The Internet of Things (IoT) is becoming ubiquitous in our daily life. IoT networks that are made up of devices low power, low memory, and low computing capability appears in many applications such as healthcare, home, agriculture. IPv6 Routing Proto
Externí odkaz:
http://arxiv.org/abs/2303.16499
We consider distributed image transmission over a noisy multiple access channel (MAC) using deep joint source-channel coding (DeepJSCC). It is known that Shannon's separation theorem holds when transmitting independent sources over a MAC in the asymp
Externí odkaz:
http://arxiv.org/abs/2211.09920
Autor:
Wilhelmi, Francesc, Hribar, Jernej, Yilmaz, Selim F., Ozfatura, Emre, Ozfatura, Kerem, Yildiz, Ozlem, Gündüz, Deniz, Chen, Hao, Ye, Xiaoying, You, Lizhao, Shao, Yulin, Dini, Paolo, Bellalta, Boris
As wireless standards evolve, more complex functionalities are introduced to address the increasing requirements in terms of throughput, latency, security, and efficiency. To unleash the potential of such new features, artificial intelligence (AI) an
Externí odkaz:
http://arxiv.org/abs/2203.10472
We consider distributed inference at the wireless edge, where multiple clients with an ensemble of models, each trained independently on a local dataset, are queried in parallel to make an accurate decision on a new sample. In addition to maximizing
Externí odkaz:
http://arxiv.org/abs/2202.03129
Autor:
Yilmaz, Selim F., Kozat, Suleyman S.
PySAD is an open-source python framework for anomaly detection on streaming data. PySAD serves various state-of-the-art methods for streaming anomaly detection. The framework provides a complete set of tools to design anomaly detection experiments ra
Externí odkaz:
http://arxiv.org/abs/2009.02572