157 citations · 248 across the 24 of their papers we have counts for
3 papers · 1 filter
Fair Wasserstein Coresets
Zikai Xiong, Niccolò Dalmasso, Shubham Sharma +5
Data distillation and coresets have emerged as popular approaches to generate a smaller representative set of samples for downstream learning tasks to handle large-scale datasets.…
FairWASP: Fast and Optimal Fair Wasserstein Pre-processing
Zikai Xiong, Niccolò Dalmasso, Alan Mishler +3
Recent years have seen a surge of machine learning approaches aimed at reducing disparities in model outputs across different subgroups. In many settings, training data may be used…
Deep Gaussian Mixture Ensembles
Yousef El-Laham, Niccolò Dalmasso, Elizabeth Fons +1
This work introduces a novel probabilistic deep learning technique called deep Gaussian mixture ensembles (DGMEs), which enables accurate quantification of both epistemic and aleat…