2 papers
cs.LG2026
Double Momentum and Error Feedback for Clipping with Fast Rates and Differential Privacy
Rustem Islamov, Samuel Horvath, Aurelien Lucchi +2
Strong Differential Privacy (DP) and Optimization guarantees are two desirable properties for a method in Federated Learning (FL). However, existing algorithms do not achieve both…
cs.CL2025
Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning
Kaustubh Ponkshe, Raghav Singhal, Eduard Gorbunov +3
Low-rank adapters have become standard for efficiently fine-tuning large language models, but they often fall short of achieving the performance of full fine-tuning. We propose a m…