1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
On the Importance of Contrastive Loss in Multimodal Learning
Yunwei Ren, Yuanzhi Li
Recently, contrastive learning approaches (e.g., CLIP (Radford et al., 2021)) have received huge success in multimodal learning, where the model tries to minimize the distance betw…
cs.LG2023
Depth Separation with Multilayer Mean-Field Networks
Yunwei Ren, Mo Zhou, Rong Ge
Depth separation -- why a deeper network is more powerful than a shallower one -- has been a major problem in deep learning theory. Previous results often focus on representation p…
stat.ML2021★ 1 cited
Understanding Deflation Process in Over-parametrized Tensor Decomposition
Rong Ge, Yunwei Ren, Xiang Wang +1
In this paper we study the training dynamics for gradient flow on over-parametrized tensor decomposition problems. Empirically, such training process often first fits larger compon…