1 citations · 3 across the 12 of their papers we have counts for
3 papers · 1 filter
Parameter-Agnostic Optimization under Relaxed Smoothness
Florian Hübler, Junchi Yang, Xiang Li +1
Tuning hyperparameters, such as the stepsize, presents a major challenge of training machine learning models. To address this challenge, numerous adaptive optimization algorithms h…
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
Liang Zhang, Junchi Yang, Amin Karbasi +1
Algorithmic reproducibility measures the deviation in outputs of machine learning algorithms upon minor changes in the training process. Previous work suggests that first-order met…
DPZero: Private Fine-Tuning of Language Models without Backpropagation
Liang Zhang, Bingcong Li, Kiran Koshy Thekumparampil +2
The widespread practice of fine-tuning large language models (LLMs) on domain-specific data faces two major challenges in memory and privacy. First, as the size of LLMs continues t…