3 citations · 9 across the 13 of their papers we have counts for
6 papers · 1 filter
Task-Driven Semantic Quantization and Imitation Learning for Goal-Oriented Communications
Yu-Chieh Chao, Yubei Chen, Weiwei Wang +4
Semantic communication marks a new paradigm shift from bit-wise data transmission to semantic information delivery for the purpose of bandwidth reduction. To more effectively carry…
LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency
Achintha Wijesinghe, Suchinthaka Wanninayaka, Weiwei Wang +3
The recent rise of semantic-style communications includes the development of goal-oriented communications (GOCOMs) remarkably efficient multimedia information transmissions. The co…
Diff-GO: Diffusion Goal-Oriented Communications to Achieve Ultra-High Spectrum Efficiency
Achintha Wijesinghe, Songyang Zhang, Suchinthaka Wanninayaka +2
The latest advances in artificial intelligence (AI) present many unprecedented opportunities to achieve much improved bandwidth saving in communications. Unlike conventional commun…
PFL-GAN: When Client Heterogeneity Meets Generative Models in Personalized Federated Learning
Achintha Wijesinghe, Songyang Zhang, Zhi Ding
Recent advances of generative learning models are accompanied by the growing interest in federated learning (FL) based on generative adversarial network (GAN) models. In the contex…
UFed-GAN: A Secure Federated Learning Framework with Constrained Computation and Unlabeled Data
Achintha Wijesinghe, Songyang Zhang, Siyu Qi +1
To satisfy the broad applications and insatiable hunger for deploying low latency multimedia data classification and data privacy in a cloud-based setting, federated learning (FL)…
PS-FedGAN: An Efficient Federated Learning Framework Based on Partially Shared Generative Adversarial Networks For Data Privacy
Achintha Wijesinghe, Songyang Zhang, Zhi Ding
Federated Learning (FL) has emerged as an effective learning paradigm for distributed computation owing to its strong potential in capturing underlying data statistics while preser…