13 citations · 72 across the 18 of their papers we have counts for
4 papers · 1 filter
Probabilistic Contrastive Principal Component Analysis
Didong Li, Andrew Jones, Barbara Engelhardt
Dimension reduction is useful for exploratory data analysis. In many applications, it is of interest to discover variation that is enriched in a "foreground" dataset relative to a…
Principal Ellipsoid Analysis (PEA): Efficient non-linear dimension reduction & clustering
Debolina Paul, Saptarshi Chakraborty, Didong Li +1
Even with the rise in popularity of over-parameterized models, simple dimensionality reduction and clustering methods, such as PCA and k-means, are still routinely used in an amazi…
Exponential-wrapped distributions on symmetric spaces
Emmanuel Chevallier, Didong Li, Yulong Lu +1
In many applications, the curvature of the space supporting the data makes the statistical modelling challenging. In this paper we discuss the construction and use of probability d…
Random Lie Brackets that Induce Torsion: A Model for Noisy Vector Fields
Didong Li, Sayan Mukherjee
We define and study a random Lie bracket that induces torsion in expectation. Almost all stochastic analysis on manifolds have assumed parallel transport. Mathematically this assum…