Hengrui Luo

Orcid: 0000-0002-9254-8342

According to our database1, Hengrui Luo authored at least 27 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
Multiple Closed Curve Modeling with Uncertainty Quantification for Shape Analysis.
SIAM/ASA J. Uncertain. Quantification, 2024

Spherical Rotation Dimension Reduction with Geometric Loss Functions.
J. Mach. Learn. Res., 2024

Non-smooth Bayesian optimization in tuning scientific applications.
Int. J. High Perform. Comput. Appl., 2024

Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data.
CoRR, 2024

A Linear-complexity Tensor Butterfly Algorithm for Compressing High-dimensional Oscillatory Integral Operators.
CoRR, 2024

Ranking Perspective for Tree-based Methods with Applications to Symbolic Feature Selection.
CoRR, 2024

Frontal Slice Approaches for Tensor Linear Systems.
CoRR, 2024

Efficient Decision Trees for Tensor Regressions.
CoRR, 2024

Tensor Decision Trees For High-Resolution Imaging Data.
Proceedings of the IEEE International Conference on Big Data, 2024

2023
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes.
CoRR, 2023

Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems.
CoRR, 2023

Sharded Bayesian Additive Regression Trees.
CoRR, 2023

Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization.
CoRR, 2023

Contrastive inverse regression for dimension reduction.
CoRR, 2023

Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software.
CoRR, 2023

Harnessing the Crowd for Autotuning High-Performance Computing Applications.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

2022
A Distance-Preserving Matrix Sketch.
J. Comput. Graph. Stat., October, 2022

Sparse Additive Gaussian Process Regression.
J. Mach. Learn. Res., 2022

Nonparametric Multi-shape Modeling with Uncertainty Quantification.
CoRR, 2022

Hybrid Models for Mixed Variables in Bayesian Optimization.
CoRR, 2022

Spherical Rotation Dimension Reduction with Geometric Loss Functions.
CoRR, 2022

2021
Non-smooth Bayesian Optimization in Tuning Problems.
CoRR, 2021

Enhancing Autotuning Capability with a History Database.
Proceedings of the 14th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2021

Combining Geometric and Topological Information for Boundary Estimation.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Topological Learning for Motion Data via Mixed Coordinates.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Generalized Penalty for Circular Coordinate Representation.
CoRR, 2020

2019
Combining Geometric and Topological Information in Image Segmentation.
CoRR, 2019


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