654 citations · 1.5k across the 37 of their papers we have counts for
8 papers · 1 filter
Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks
Peyman Tehrani, Francesco Restuccia, Marco Levorato
Next Generation (NextG) networks are expected to support demanding tactile internet applications such as augmented reality and connected autonomous vehicles. Whereas recent innovat…
Spatio-Temporal Split Learning for Autonomous Aerial Surveillance using Urban Air Mobility (UAM) Networks
Yoo Jeong Ha, Soyi Jung, Jae-Hyun Kim +2
Autonomous surveillance unmanned aerial vehicles (UAVs) are deployed to observe the streets of the city for any suspicious activities. This paper utilizes surveillance UAVs for the…
Data Collection and Labeling of Real-Time IoT-Enabled Bio-Signals in Everyday Settings for Mental Health Improvement
Ali Tazarv, Sina Labbaf, Amir M. Rahmani +2
Real-time physiological data collection and analysis play a central role in modern well-being applications. Personalized classifiers and detectors have been shown to outperform gen…
Supervised Compression for Resource-Constrained Edge Computing Systems
Yoshitomo Matsubara, Ruihan Yang, Marco Levorato +1
There has been much interest in deploying deep learning algorithms on low-powered devices, including smartphones, drones, and medical sensors. However, full-scale deep neural netwo…
Personalized Stress Monitoring using Wearable Sensors in Everyday Settings
Ali Tazarv, Sina Labbaf, Stephanie M. Reich +3
Since stress contributes to a broad range of mental and physical health problems, the objective assessment of stress is essential for behavioral and physiological studies. Although…
A Deep Learning Approach to Predict Blood Pressure from PPG Signals
Ali Tazarv, Marco Levorato
Blood Pressure (BP) is one of the four primary vital signs indicating the status of the body's vital (life-sustaining) functions. BP is difficult to continuously monitor using a sp…