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cs.LG2026
Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data
Xuanyu Chen, Nan Yang, Shuai Wang +1
Recent research has introduced distributed self-supervised learning (D-SSL) approaches to leverage vast amounts of unlabeled decentralized data. However, D-SSL faces the critical c…
cs.LG2025
Scaling Law Analysis in Federated Learning: How to Select the Optimal Model Size?
Xuanyu Chen, Nan Yang, Shuai Wang +1
The recent success of large language models (LLMs) has sparked a growing interest in training large-scale models. As the model size continues to scale, concerns are growing about t…
cs.LG2025
Optimal Look-back Horizon for Time Series Forecasting in Federated Learning
Dahao Tang, Nan Yang, Yanli Li +3
Selecting an appropriate look-back horizon remains a fundamental challenge in time series forecasting (TSF), particularly in the federated learning scenarios where data is decentra…