Zobrazeno 1 - 10
of 17 039
pro vyhledávání: '"Gunduz, A"'
We propose a novel integrated sensing and communication (ISAC) system, where the base station (BS) passively senses the channel parameters using the information carrying signals from a user. To simultaneously guarantee decoding and sensing performanc
Externí odkaz:
http://arxiv.org/abs/2411.05531
We propose a novel deep learning based method to design a coded waveform for integrated sensing and communication (ISAC) system based on orthogonal frequency-division multiplexing (OFDM). Our ultimate goal is to design a coded waveform, which is capa
Externí odkaz:
http://arxiv.org/abs/2410.10711
The restless multi-armed bandit (RMAB) framework is a popular model with applications across a wide variety of fields. However, its solution is hindered by the exponentially growing state space (with respect to the number of arms) and the combinatori
Externí odkaz:
http://arxiv.org/abs/2408.09882
Segmenting multiple objects (e.g., organs) in medical images often requires an understanding of their topology, which simultaneously quantifies the shape of the objects and their positions relative to each other. This understanding is important for s
Externí odkaz:
http://arxiv.org/abs/2408.08038
Road traffic congestion prediction is a crucial component of intelligent transportation systems, since it enables proactive traffic management, enhances suburban experience, reduces environmental impact, and improves overall safety and efficiency. Al
Externí odkaz:
http://arxiv.org/abs/2408.01016
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
Graphs are crucial for representing interrelated data and aiding predictive modeling by capturing complex relationships. Achieving high-quality graph representation is important for identifying linked patterns, leading to improvements in Graph Neural
Externí odkaz:
http://arxiv.org/abs/2407.14765
Federated learning (FL) has been introduced to enable a large number of clients, possibly mobile devices, to collaborate on generating a generalized machine learning model thanks to utilizing a larger number of local samples without sharing to offer
Externí odkaz:
http://arxiv.org/abs/2404.06230
Autor:
Islek, Irem, Oguducu, Sule Gunduz
Recommendation systems can provide accurate recommendations by analyzing user shopping history. A richer user history results in more accurate recommendations. However, in real applications, users prefer e-commerce platforms where the item they seek
Externí odkaz:
http://arxiv.org/abs/2403.12096
We introduce deep joint source-channel coding (DeepJSCC) schemes for image transmission over cooperative relay channels. The relay either amplifies-and-forwards its received signal, called DeepJSCC-AF, or leverages neural networks to extract relevant
Externí odkaz:
http://arxiv.org/abs/2403.10613