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Found 6 papers, 0 papers with code
Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning
In this paper, we provide a thorough study on an effective integration of HFL and VFL, to achieve communication efficiency and overcome the above limitations when data is both horizontally and vertically partitioned.
Autonomous Platoon Control with Integrated Deep Reinforcement Learning and Dynamic Programming
Deep Reinforcement Learning (DRL) is regarded as a potential method for car-following control and has been mostly studied to support a single following vehicle.
SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks
There is a growing demand for high-resolution (HR) medical images in both the clinical and research applications.
Self-Renormalization of Quasi-Light-Front Correlators on the Lattice
In applying large-momentum effective theory, renormalization of the Euclidean correlators in lattice regularization is a challenge due to linear divergences in the self-energy of Wilson lines.
High Energy Physics - Lattice High Energy Physics - Phenomenology
LSTM-based Anomaly Detection for Non-linear Dynamical System
Anomaly detection for non-linear dynamical system plays an important role in ensuring the system stability.
Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
Next, a comprehensive survey of the state-of-art research on DRL for AIoT is presented, where the existing works are classified and summarized under the umbrella of the proposed general DRL model.
