4 citations · 5 across the 5 of their papers we have counts for
4 papers · 1 filter
Adversarial Classification of the Attacks on Smart Grids Using Game Theory and Deep Learning
Kian Hamedani, Lingjia Liu, Jithin Jagannath +2
Smart grids are vulnerable to cyber-attacks. This paper proposes a game-theoretic approach to evaluate the variations caused by an attacker on the power measurements. Adversaries c…
Differential Privacy Meets Federated Learning under Communication Constraints
Nima Mohammadi, Jianan Bai, Qiang Fan +3
The performance of federated learning systems is bottlenecked by communication costs and training variance. The communication overhead problem is usually addressed by three communi…
Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond
Hao-Hsuan Chang, Lingjia Liu, Yang Yi
Deep reinforcement learning (DRL) has been shown to be successful in many application domains. Combining recurrent neural networks (RNNs) and DRL further enables DRL to be applicab…
Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach
Hao-Hsuan Chang, Hao Song, Yang Yi +3
Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to share radio spectrum among different networks. As a secondary user (SU), a DSA device will fac…