166 citations · 644 across the 58 of their papers we have counts for
4 papers · 2 filters
Run Away From your Teacher: Understanding BYOL by a Novel Self-Supervised Approach
Haizhou Shi, Dongliang Luo, Siliang Tang +2
Recently, a newly proposed self-supervised framework Bootstrap Your Own Latent (BYOL) seriously challenges the necessity of negative samples in contrastive learning frameworks. BYO…
Federated Unsupervised Representation Learning
Fengda Zhang, Kun Kuang, Zhaoyang You +6
To leverage enormous unlabeled data on distributed edge devices, we formulate a new problem in federated learning called Federated Unsupervised Representation Learning (FURL) to le…
Stable Prediction via Leveraging Seed Variable
Kun Kuang, Bo Li, Peng Cui +4
In this paper, we focus on the problem of stable prediction across unknown test data, where the test distribution is agnostic and might be totally different from the training one.…
Balance-Subsampled Stable Prediction
Kun Kuang, Hengtao Zhang, Fei Wu +2
In machine learning, it is commonly assumed that training and test data share the same population distribution. However, this assumption is often violated in practice because the s…