5 papers
Disentanglement with Holographic Reduced Representations
Jhonny J. Velasquez Olivera, Christo K. Thomas, Walid Saad
Disentanglement, the separation of factors of variation in data using neural networks, remains a long-standing challenge in machine learning. Prior work has addressed this problem…
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…
Rate-Distortion-Perception Theory for Semantic Communication
Jingxuan Chai, Yong Xiao, Guangming Shi +1
Semantic communication has attracted significant interest recently due to its capability to meet the fast growing demand on user-defined and human-oriented communication services s…
Physical-Layer Semantic-Aware Network for Zero-Shot Wireless Sensing
Huixiang Zhu, Yong Xiao, Yingyu Li +2
Device-free wireless sensing has recently attracted significant interest due to its potential to support a wide range of immersive human-machine interactive applications. However,…
Intelligible Protocol Learning for Resource Allocation in 6G O-RAN Slicing
Farhad Rezazadeh, Hatim Chergui, Shuaib Siddiqui +4
An adaptive standardized protocol is essential for addressing inter-slice resource contention and conflict in network slicing. Traditional protocol standardization is a cumbersome…