GQ-FSL: Green Quantized Federated Split Learning
The episode discusses the paper "GQ-FSL: Green Quantized Federated Split Learning," which addresses high energy consumption in standard federated split learning. The authors propose a framework using stochastic quantization and asymmetric precision to reduce the physical footprint of training on mobile devices. Results show superior energy efficiency compared to traditional methods, enabling sustainable AI deployment across large networks.