66 citations · 300 across the 29 of their papers we have counts for
5 papers · 1 filter
Greedy Modality Selection via Approximate Submodular Maximization
Runxiang Cheng, Gargi Balasubramaniam, Yifei He +2
Multimodal learning considers learning from multi-modality data, aiming to fuse heterogeneous sources of information. However, it is not always feasible to leverage all available m…
Conditional Supervised Contrastive Learning for Fair Text Classification
Jianfeng Chi, William Shand, Yaodong Yu +3
Contrastive representation learning has gained much attention due to its superior performance in learning representations from both image and sequential data. However, the learned…
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond
Haoxiang Wang, Bo Li, Han Zhao
The vast majority of existing algorithms for unsupervised domain adaptation (UDA) focus on adapting from a labeled source domain to an unlabeled target domain directly in a one-off…
Conditional Contrastive Learning with Kernel
Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma +4
Conditional contrastive learning frameworks consider the conditional sampling procedure that constructs positive or negative data pairs conditioned on specific variables. Fair cont…
Provable Domain Generalization via Invariant-Feature Subspace Recovery
Haoxiang Wang, Haozhe Si, Bo Li +1
Domain generalization asks for models trained over a set of training environments to perform well in unseen test environments. Recently, a series of algorithms such as Invariant Ri…