4 papers
Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
Rachael Hwee Ling Sim, Jue Fan, Xiao Tian +3
Collaborative machine learning involves training high-quality models using datasets from a number of sources. To incentivize sources to share data, existing data valuation methods…
Is Data Shapley Not Better than Random in Data Selection? Ask NASH
Xiao Tian, Jue Fan, Rachael Hwee Ling Sim +3
Data selection studies the problem of identifying high-quality subsets of training data. While some existing works have considered selecting the subset of data with top- Data Sh…
INO-SGD: Addressing Utility Imbalance under Individualized Differential Privacy
Xiao Tian, Jue Fan, Rachael Hwee Ling Sim +1
Differential privacy (DP) is widely employed in machine learning to protect confidential or sensitive training data from being revealed. As data owners gain greater control over th…
DeRDaVa: Deletion-Robust Data Valuation for Machine Learning
Xiao Tian, Rachael Hwee Ling Sim, Jue Fan +1
Data valuation is concerned with determining a fair valuation of data from data sources to compensate them or to identify training examples that are the most or least useful for pr…