12 citations · 28 across the 13 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.LG2023★ 3 cited
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics
Jiacheng Zhu, Jielin Qiu, Aritra Guha +4
We propose to study and promote the robustness of a model as per its performance through the interpolation of training data distributions. Specifically, (1) we augment the data by…
math.ST2023★ 1 cited
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances
Aritra Guha, Nhat Ho, XuanLong Nguyen
Dirichlet Process mixture models (DPMM) in combination with Gaussian kernels have been an important modeling tool for numerous data domains arising from biological, physical, and s…