1 citations · 1 across the 4 of their papers we have counts for
4 papers
The Effect of Training Task Diversity on In-Context Learning through the Lens of Low-Dimensional Subspaces
Soo Min Kwon, Alec S. Xu, Can Yaras +3
The transformer's emergent ability to perform in-context learning (ICL) has sparked a wide range of studies designed to understand its underlying mechanisms. Existing works often s…
Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD?
Jihwan Kim, Dogyoon Song, Chulhee Yun
We study scaling laws of signSGD under a power-law random features (PLRF) model that accounts for both feature and target decay. We analyze the population risk of a linear model tr…
Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures
Huijie Zhang, Yifu Lu, Ismail Alkhouri +3
Diffusion models, emerging as powerful deep generative tools, excel in various applications. They operate through a two-steps process: introducing noise into training samples and t…
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics
Soo Min Kwon, Zekai Zhang, Dogyoon Song +2
Overparameterized models have proven to be powerful tools for solving various machine learning tasks. However, overparameterization often leads to a substantial increase in computa…