The Gaussian process (GP) is a popular statistical technique for stochas...
Algorithms from Randomized Numerical Linear Algebra (RandNLA) are known ...
In this paper we develop the randomized Sharded Bayesian Additive Regres...
We introduce an efficient and robust auto-tuning framework for hyperpara...
Supervised dimension reduction (SDR) has been a topic of growing interes...
The modeling and uncertainty quantification of closed curves is an impor...
Modern datasets witness high-dimensionality and nontrivial geometries of...
The statistical methods used to analyze medical data are becoming
increa...
Visualizing very large matrices involves many formidable problems. Vario...
Topological data analysis (TDA) allows us to explore the topological fea...
Topological Data Analysis (TDA) provides novel approaches that allow us ...
A fundamental problem in computer vision is image segmentation, where th...
In this paper we introduce a novel model for Gaussian process (GP) regre...