2 citations · 2 across the 4 of their papers we have counts for
4 papers
QnRL: Quantum-Native Reinforcement Learning
Alexander DeRieux, Walid Saad
Quantum reinforcement learning (QRL) is a promising approach to learn effective decision strategies across several applications with stochastic environments. Instead of directly mo…
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
Alexander DeRieux, Walid Saad
Collaboration is a key challenge in distributed multi-agent reinforcement learning (MARL) environments. Learning frameworks for these decentralized systems must weigh the benefits…
A Bargaining Game for Personalized, Energy Efficient Split Learning over Wireless Networks
Minsu Kim, Alexander DeRieux, Walid Saad
Split learning (SL) is an emergent distributed learning framework which can mitigate the computation and wireless communication overhead of federated learning. It splits a machine…
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart Cities
Alexander C. DeRieux, Walid Saad, Wangda Zuo +3
Rapid global urbanization is a double-edged sword, heralding promises of economical prosperity and public health while also posing unique environmental and humanitarian challenges.…