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cs.CV2026
Fine-Tuning Impairs the Balancedness of Foundation Models in Long-tailed Personalized Federated Learning
Shihao Hou, Chikai Shang, Zhiheng Yang +5
Personalized federated learning (PFL) with foundation models has emerged as a promising paradigm enabling clients to adapt to heterogeneous data distributions. However, real-world…
cs.CV2025
Progressive Data Dropout: An Embarrassingly Simple Approach to Faster Training
Shriram M Sathiyanarayanan, Xinyue Hao, Shihao Hou +4
The success of the machine learning field has reliably depended on training on large datasets. While effective, this trend comes at an extraordinary cost. This is due to two deeply…