436 citations · 763 across the 12 of their papers we have counts for
4 papers · 1 filter
Cross-Domain Sentiment Classification with In-Domain Contrastive Learning
Tian Li, Xiang Chen, Shanghang Zhang +2
Contrastive learning (CL) has been successful as a powerful representation learning method. In this paper, we propose a contrastive learning framework for cross-domain sentiment cl…
Ditto: Fair and Robust Federated Learning Through Personalization
Tian Li, Shengyuan Hu, Ahmad Beirami +1
Fairness and robustness are two important concerns for federated learning systems. In this work, we identify that robustness to data and model poisoning attacks and fairness, measu…
Cross-Domain Sentiment Classification with Contrastive Learning and Mutual Information Maximization
Tian Li, Xiang Chen, Shanghang Zhang +2
Contrastive learning (CL) has been successful as a powerful representation learning method. In this work we propose CLIM: Contrastive Learning with mutual Information Maximization,…
Tilted Empirical Risk Minimization
Tian Li, Ahmad Beirami, Maziar Sanjabi +1
Empirical risk minimization (ERM) is typically designed to perform well on the average loss, which can result in estimators that are sensitive to outliers, generalize poorly, or tr…