Search Results for author: Hengrui Luo

Found 14 papers, 8 papers with code

A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes

no code implementations18 Sep 2023 Marcus M. Noack, Hengrui Luo, Mark D. Risser

The Gaussian process (GP) is a popular statistical technique for stochastic function approximation and uncertainty quantification from data.

Gaussian Processes Uncertainty Quantification

Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems

no code implementations30 Aug 2023 Younghyun Cho, James W. Demmel, Michał Dereziński, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley J. Murray

Algorithms from Randomized Numerical Linear Algebra (RandNLA) are known to be effective in handling high-dimensional computational problems, providing high-quality empirical performance as well as strong probabilistic guarantees.

regression

Sharded Bayesian Additive Regression Trees

no code implementations1 Jun 2023 Hengrui Luo, Matthew T. Pratola

In this paper we develop the randomized Sharded Bayesian Additive Regression Trees (SBT) model.

regression

Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization

no code implementations1 Jun 2023 Yin-Ting Liao, Hengrui Luo, Anna Ma

We introduce an efficient and robust auto-tuning framework for hyperparameter selection in dimension reduction (DR) algorithms, focusing on large-scale datasets and arbitrary performance metrics.

Bayesian Optimization Dimensionality Reduction

Contrastive inverse regression for dimension reduction

no code implementations20 May 2023 Sam Hawke, Hengrui Luo, Didong Li

Supervised dimension reduction (SDR) has been a topic of growing interest in data science, as it enables the reduction of high-dimensional covariates while preserving the functional relation with certain response variables of interest.

Dimensionality Reduction regression

Nonparametric Multi-shape Modeling with Uncertainty Quantification

no code implementations18 Jun 2022 Hengrui Luo, Justin D. Strait

The modeling and uncertainty quantification of closed curves is an important problem in the field of shape analysis, and can have significant ramifications for subsequent statistical tasks.

Uncertainty Quantification

Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization

1 code implementation3 Jun 2022 Hengrui Luo, Younghyun Cho, James W. Demmel, Xiaoye S. Li, Yang Liu

This paper presents a new type of hybrid model for Bayesian optimization (BO) adept at managing mixed variables, encompassing both quantitative (continuous and integer) and qualitative (categorical) types.

Bayesian Optimization Gaussian Processes +2

Spherical Rotation Dimension Reduction with Geometric Loss Functions

1 code implementation23 Apr 2022 Hengrui Luo, Jeremy E. Purvis, Didong Li

Modern datasets often exhibit high dimensionality, yet the data reside in low-dimensional manifolds that can reveal underlying geometric structures critical for data analysis.

Dimensionality Reduction

Non-smooth Bayesian Optimization in Tuning Problems

1 code implementation15 Sep 2021 Hengrui Luo, James W. Demmel, Younghyun Cho, Xiaoye S. Li, Yang Liu

By using this surrogate model, we want to capture the non-smoothness of the black-box function.

Bayesian Optimization

A Distance-preserving Matrix Sketch

1 code implementation8 Sep 2020 Leland Wilkinson, Hengrui Luo

This selection is designed to preserve relative distances as closely as possible.

Clustering feature selection +1

Generalized Penalty for Circular Coordinate Representation

1 code implementation3 Jun 2020 Hengrui Luo, Alice Patania, Jisu Kim, Mikael Vejdemo-Johansson

We provide simulation experiments and real data analysis to support our claim that circular coordinates with generalized penalty will detect the change in high-dimensional datasets under different sampling schemes while preserving the topological structures.

Data Visualization Dimensionality Reduction +1

Combining Geometric and Topological Information for Boundary Estimation

1 code implementation10 Oct 2019 Hengrui Luo, Justin Strait

In the presence of images featuring objects with complex topological structures, such as objects with holes or multiple objects, the user must initialize separate curves for each boundary of interest.

Boundary Detection Clustering +1

Sparse Additive Gaussian Process Regression

1 code implementation23 Aug 2019 Hengrui Luo, Giovanni Nattino, Matthew T. Pratola

In this paper we introduce a novel model for Gaussian process (GP) regression in the fully Bayesian setting.

Statistics Theory Statistics Theory

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