44 citations · 80 across the 4 of their papers we have counts for
5 papers
SGD with shuffling: optimal rates without component convexity and large epoch requirements
Kwangjun Ahn, Chulhee Yun, Suvrit Sra
We study without-replacement SGD for solving finite-sum optimization problems. Specifically, depending on how the indices of the finite-sum are shuffled, we consider the RandomShuf…
Minimum Width for Universal Approximation
Sejun Park, Chulhee Yun, Jaeho Lee +1
The universal approximation property of width-bounded networks has been studied as a dual of classical universal approximation results on depth-bounded networks. However, the criti…
Low-Rank Bottleneck in Multi-head Attention Models
Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat +2
Attention based Transformer architecture has enabled significant advances in the field of natural language processing. In addition to new pre-training techniques, recent improvemen…
Are Transformers universal approximators of sequence-to-sequence functions?
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat +2
Despite the widespread adoption of Transformer models for NLP tasks, the expressive power of these models is not well-understood. In this paper, we establish that Transformer model…
Are deep ResNets provably better than linear predictors?
Chulhee Yun, Suvrit Sra, Ali Jadbabaie
Recent results in the literature indicate that a residual network (ResNet) composed of a single residual block outperforms linear predictors, in the sense that all local minima in…