2 papers
cs.LG2025
Can Textual Gradient Work in Federated Learning?
Minghui Chen, Ruinan Jin, Wenlong Deng +4
Recent studies highlight the promise of LLM-based prompt optimization, especially with TextGrad, which automates differentiation'' via texts and backpropagates textual feedback. Th…
cs.DC2024
Federated Graph Learning with Adaptive Importance-based Sampling
Anran Li, Yuanyuan Chen, Chao Ren +5
For privacy-preserving graph learning tasks involving distributed graph datasets, federated learning (FL)-based GCN (FedGCN) training is required. A key challenge for FedGCN is sca…