Time-varying convex optimization: Time-structured algorithms and applications
Optimization underpins many of the challenges that science and technology face on a daily
basis. Recent years have witnessed a major shift from traditional optimization paradigms …
basis. Recent years have witnessed a major shift from traditional optimization paradigms …
Federated learning via over-the-air computation
The stringent requirements for low-latency and privacy of the emerging high-stake
applications with intelligent devices such as drones and smart vehicles make the cloud …
applications with intelligent devices such as drones and smart vehicles make the cloud …
Deep learning at the physical layer: System challenges and applications to 5G and beyond
F Restuccia, T Melodia - IEEE Communications Magazine, 2020 - ieeexplore.ieee.org
The unprecedented requirements of IoT have made fine-grained optimization of spectrum
resources an urgent necessity. Thus, designing techniques able to extract knowledge from …
resources an urgent necessity. Thus, designing techniques able to extract knowledge from …
Model-based machine learning for communications
Traditional communication systems design is dominated by methods that are based on
statistical models. These statistical-model-based algorithms, which we refer to henceforth as …
statistical models. These statistical-model-based algorithms, which we refer to henceforth as …
DeepWiERL: Bringing deep reinforcement learning to the internet of self-adaptive things
F Restuccia, T Melodia - IEEE INFOCOM 2020-IEEE …, 2020 - ieeexplore.ieee.org
Recent work has demonstrated that cutting-edge advances in deep reinforcement learning
(DRL) may be leveraged to empower wireless devices with the much-needed ability to" …
(DRL) may be leveraged to empower wireless devices with the much-needed ability to" …
Machine learning and intelligent communications
XL Huang, X Ma, F Hu - Mobile Networks and Applications, 2018 - Springer
Along with the fast developing of mobile communications technologies, the amount of high
quality wireless services is required and increasing exponentially. According to the …
quality wireless services is required and increasing exponentially. According to the …
Toward intelligent network optimization in wireless networking: An auto-learning framework
In wireless communication systems (WCSs), the network optimization problems (NOPs) play
an important role in maximizing system performance by setting appropriate network …
an important role in maximizing system performance by setting appropriate network …
Goal-oriented communication for edge learning based on the information bottleneck
F Pezone, S Barbarossa… - ICASSP 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Whenever communication takes place to fulfill a goal, an effective way to encode the source
data to be transmitted is to use an encoding rule that allows the receiver to meet the …
data to be transmitted is to use an encoding rule that allows the receiver to meet the …
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …