research
∙
09/18/2023
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes
The Gaussian process (GP) is a popular statistical technique for stochas...
share
research
∙
08/30/2023
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems
Algorithms from Randomized Numerical Linear Algebra (RandNLA) are known ...
research
∙
06/01/2023
Sharded Bayesian Additive Regression Trees
In this paper we develop the randomized Sharded Bayesian Additive Regres...
research
∙
06/01/2023
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization
We introduce an efficient and robust auto-tuning framework for hyperpara...
research
∙
05/20/2023
Contrastive inverse regression for dimension reduction
Supervised dimension reduction (SDR) has been a topic of growing interes...
research
∙
06/18/2022
Nonparametric Multi-shape Modeling with Uncertainty Quantification
The modeling and uncertainty quantification of closed curves is an impor...
research
∙
04/23/2022
Spherical Rotation Dimension Reduction with Geometric Loss Functions
Modern datasets witness high-dimensionality and nontrivial geometries of...
research
∙
11/01/2021
Computing with R-INLA: Accuracy and reproducibility with implications for the analysis of COVID-19 data
The statistical methods used to analyze medical data are becoming increa...
research
∙
09/08/2020
A Distance-preserving Matrix Sketch
Visualizing very large matrices involves many formidable problems. Vario...
research
∙
06/03/2020
Asymptotics of Lower Dimensional Zero-Density Regions
Topological data analysis (TDA) allows us to explore the topological fea...
research
∙
06/03/2020
Generalized Penalty for Circular Coordinate Representation
Topological Data Analysis (TDA) provides novel approaches that allow us ...
research
∙
10/10/2019
Combining Geometric and Topological Information in Image Segmentation
A fundamental problem in computer vision is image segmentation, where th...
research
∙
08/23/2019
