16 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Is Pre-training Truly Better Than Meta-Learning?
Brando Miranda, Patrick Yu, Saumya Goyal +2
In the context of few-shot learning, it is currently believed that a fixed pre-trained (PT) model, along with fine-tuning the final layer during evaluation, outperforms standard me…
cs.LG2022
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence
Brando Miranda, Patrick Yu, Yu-Xiong Wang +1
Recently, it has been observed that a transfer learning solution might be all we need to solve many few-shot learning benchmarks -- thus raising important questions about when and…
cs.LG2018★ 16 cited
LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning
Hsin-Pai Cheng, Patrick Yu, Haojing Hu +4
Distributed learning systems have enabled training large-scale models over large amount of data in significantly shorter time. In this paper, we focus on decentralized distributed…