3 citations · 3 across the 2 of their papers we have counts for
2 papers
math.OC2026
Decentralized Learning with Dynamically Refined Edge Weights: A Data-Dependent Framework
Rongxing Du, Hoi-To Wai
This paper aims to accelerate decentralized optimization by strategically designing the edge weights used in the agent-to-agent message exchanges. We propose a Dynamic Directed Dec…
cs.LG2024★ 3 cited
Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs
Feiyang Kang, Hoang Anh Just, Yifan Sun +5
This work focuses on leveraging and selecting from vast, unlabeled, open data to pre-fine-tune a pre-trained language model. The goal is to minimize the need for costly domain-spec…