4 papers
Sensing and Storing Less: A MARL-based Solution for Energy Saving in Edge Internet of Things
Zongyang Yuan, Lailong Luo, Qianzhen Zhang +3
As the number of Internet of Things (IoT) devices continuously grows and application scenarios constantly enrich, the volume of sensor data experiences an explosive increase. Howev…
Communication and Computation Efficient Split Federated Learning in O-RAN
Shunxian Gu, Chaoqun You, Bangbang Ren +1
The hierarchical architecture of Open Radio Access Network (O-RAN) has enabled a new Federated Learning (FL) paradigm that trains models using data from non- and near-real-time (ne…
DHO: Accelerating Distributed Hybrid Order Optimization via Model Parallelism and ADMM
Shunxian Gu, Chaoqun You, Bangbang Ren +3
Scaling deep neural network (DNN) training to more devices can reduce time-to-solution. However, it is impractical for users with limited computing resources. FOSI, as a hybrid ord…
Analytic Personalized Federated Meta-Learning
Shunxian Gu, Chaoqun You, Deke Guo +4
Analytic Federated Learning (AFL) is an enhanced gradient-free federated learning (FL) paradigm designed to accelerate training by updating the global model in a single step with c…