Hengrui Luo

According to our database, Hengrui Luo authored at least 33 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Minimizing the Arithmetic and Communication Complexity of Jacobi's Method for Eigenvalues and Singular Values.

James Demmel, Hengrui Luo, Ryan Schneider, Yifu Wang

CoRR, June, 2025

Parallel GPU-Accelerated Randomized Construction of Approximate Cholesky Preconditioners.

Tianyu Liang, Chao Chen, Yotam Yaniv, Hengrui Luo, David Tench, Xiaoye S. Li, Aydin Buluç, James Demmel

CoRR, May, 2025

EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data.

Jason Han, Nicholas S. DiBrita, Younghyun Cho, Hengrui Luo, Tirthak Patel

CoRR, March, 2025

Kernel-based estimators for functional causal effects.

Yordan P. Raykov, Hengrui Luo, Justin D. Strait, Wasiur R. KhudaBukhsh

CoRR, March, 2025

Asymptotic Optimism of Random-Design Linear and Kernel Regression Models.

Hengrui Luo, Yunzhang Zhu

CoRR, February, 2025

Surrogate-Based Autotuning for Randomized Sketching Algorithms in Regression Problems.

Younghyun Cho, James Demmel, Michal Derezinski, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley Murray

SIAM J. Matrix Anal. Appl., 2025

2024

Multiple Closed Curve Modeling with Uncertainty Quantification for Shape Analysis.

Hengrui Luo, Justin D. Strait

SIAM/ASA J. Uncertain. Quantification, 2024

Spherical Rotation Dimension Reduction with Geometric Loss Functions.

Hengrui Luo, Jeremy E. Purvis, Didong Li

J. Mach. Learn. Res., 2024

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

Hengrui Luo, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu

J. Comput. Graph. Stat., 2024

Non-smooth Bayesian optimization in tuning scientific applications.

Hengrui Luo, Younghyun Cho, James Weldon Demmel, Igor Kozachenko, Xiaoye S. Li, Yang Liu

Int. J. High Perform. Comput. Appl., 2024

Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data.

Mark D. Risser, Marcus Michael Noack, Hengrui Luo, Ronald Pandolfi

CoRR, 2024

A Linear-complexity Tensor Butterfly Algorithm for Compressing High-dimensional Oscillatory Integral Operators.

P. Michael Kielstra, Tianyi Shi, Hengrui Luo, Jianliang Qian, Yang Liu

CoRR, 2024

Ranking Perspective for Tree-based Methods with Applications to Symbolic Feature Selection.

Hengrui Luo, Meng Li

CoRR, 2024

Frontal Slice Approaches for Tensor Linear Systems.

Hengrui Luo, Anna Ma

CoRR, 2024

Efficient Decision Trees for Tensor Regressions.

Hengrui Luo, Akira Horiguchi, Li Ma

CoRR, 2024

Tensor Decision Trees For High-Resolution Imaging Data.

Zhihao Chen, Hengrui Luo, Suprateek Kundu, Marina Vannucci

Proceedings of the IEEE International Conference on Big Data, 2024

2023

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

Marcus Michael Noack, Hengrui Luo, Mark D. Risser

CoRR, 2023

Sharded Bayesian Additive Regression Trees.

Hengrui Luo, Matthew T. Pratola

CoRR, 2023

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

Yin-Ting Liao, Hengrui Luo, Anna Ma

CoRR, 2023

Contrastive inverse regression for dimension reduction.

Sam Hawke, Hengrui Luo, Didong Li

CoRR, 2023

Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software.

Riley Murray, James Demmel, Michael W. Mahoney, N. Benjamin Erichson, Maksim Melnichenko, Osman Asif Malik, Laura Grigori, Piotr Luszczek, Michal Derezinski, Miles E. Lopes, Tianyu Liang, Hengrui Luo, Jack J. Dongarra

CoRR, 2023

Harnessing the Crowd for Autotuning High-Performance Computing Applications.

Younghyun Cho, James Weldon Demmel, Jacob King, Xiaoye S. Li, Yang Liu, Hengrui Luo

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

2022

A Distance-Preserving Matrix Sketch.

Leland Wilkinson, Hengrui Luo

J. Comput. Graph. Stat., October, 2022

Sparse Additive Gaussian Process Regression.

Hengrui Luo, Giovanni Nattino, Matthew T. Pratola

J. Mach. Learn. Res., 2022

Nonparametric Multi-shape Modeling with Uncertainty Quantification.

Hengrui Luo, Justin D. Strait

CoRR, 2022

Hybrid Models for Mixed Variables in Bayesian Optimization.

Hengrui Luo, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu

CoRR, 2022

Spherical Rotation Dimension Reduction with Geometric Loss Functions.

Hengrui Luo, Didong Li

CoRR, 2022

2021

Non-smooth Bayesian Optimization in Tuning Problems.

Hengrui Luo, James Weldon Demmel, Younghyun Cho, Xiaoye S. Li, Yang Liu

CoRR, 2021

Enhancing Autotuning Capability with a History Database.

Younghyun Cho, James Demmel, Xiaoye S. Li, Yang Liu, Hengrui Luo

Proceedings of the 14th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2021

Combining Geometric and Topological Information for Boundary Estimation.

Hengrui Luo, Justin D. Strait

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Topological Learning for Motion Data via Mixed Coordinates.

Hengrui Luo, Jisu Kim, Alice Patania, Mikael Vejdemo-Johansson

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Generalized Penalty for Circular Coordinate Representation.

Hengrui Luo, Alice Patania, Jisu Kim, Mikael Vejdemo-Johansson

CoRR, 2020

2019

Combining Geometric and Topological Information in Image Segmentation.

Hengrui Luo, Justin D. Strait, Abhijoy Saha

CoRR, 2019