Hengrui Luo - RankMe

44 papers A* 1A 1B 1Journal 38Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Asymptotic Optimism for Tensor Regression Models with Applications to Neural Network Compression. CoRR Haoming Shi, Eric C. Chi, Hengrui Luo
2026	J	`jnl`	GGMPs: Generalized Gaussian Mixture Processes. CoRR Vardaan Tekriwal, Mark D. Risser, Hengrui Luo, Marcus Michael Noack
2026	J	`jnl`	Robust Bayesian Optimization via Tempered Posteriors. CoRR Jiguang Li, Hengrui Luo
2026	J	`jnl`	Wasserstein-type Gaussian Process Regressions for Input Measurement Uncertainty. CoRR Hengrui Luo, Xiaoye S. Li, Yang Liu, Marcus Noack, Ji Qiang, Mark D. Risser
2026	J	`jnl`	Wedge Sampling: Efficient Tensor Completion with Nearly-Linear Sample Complexity. CoRR Hengrui Luo, Anna Ma, Ludovic Stephan, Yizhe Zhu
2025	J	`jnl`	A Linear-Complexity Tensor Butterfly Algorithm for Compressing High-Dimensional Oscillatory Integral Operators. Multiscale Model. Simul. P. Michael Kielstra, Tianyi Shi, Hengrui Luo, Jianliang Qian, Yang Liu
2025	J	`jnl`	Asymptotic Optimism of Random-Design Linear and Kernel Regression Models. CoRR Hengrui Luo, Yunzhang Zhu
2025	A*	`conf`	EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data. DAC Jason Han, Nicholas S. DiBrita, Younghyun Cho, Hengrui Luo, Tirthak Patel
2025	J	`jnl`	EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data. CoRR Jason Han, Nicholas S. DiBrita, Younghyun Cho, Hengrui Luo, Tirthak Patel
2025	J	`jnl`	Kernel-based estimators for functional causal effects. CoRR Yordan P. Raykov, Hengrui Luo, Justin D. Strait, Wasiur R. KhudaBukhsh
2025	J	`jnl`	Minimizing the Arithmetic and Communication Complexity of Jacobi's Method for Eigenvalues and Singular Values. CoRR James Demmel, Hengrui Luo, Ryan Schneider, Yifu Wang
2025	J	`jnl`	Parallel GPU-Accelerated Randomized Construction of Approximate Cholesky Preconditioners. CoRR Tianyu Liang, Chao Chen, Yotam Yaniv, Hengrui Luo, David Tench, Xiaoye S. Li, Aydin Buluç, James Demmel
2025	J	`jnl`	Surrogate-Based Autotuning for Randomized Sketching Algorithms in Regression Problems. SIAM J. Matrix Anal. Appl. Younghyun Cho, James Demmel, Michal Derezinski, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley Murray
2025	J	`jnl`	gp2Scale: A Class of Compactly-Supported Non-Stationary Kernels and Distributed Computing for Exact Gaussian Processes on 10 Million Data Points. CoRR Marcus Michael Noack, Mark D. Risser, Hengrui Luo, Vardaan Tekriwal, Ronald Pandolfi
2024	J	`jnl`	A Linear-complexity Tensor Butterfly Algorithm for Compressing High-dimensional Oscillatory Integral Operators. CoRR P. Michael Kielstra, Tianyi Shi, Hengrui Luo, Jianliang Qian, Yang Liu
2024	J	`jnl`	Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data. CoRR Mark D. Risser, Marcus Michael Noack, Hengrui Luo, Ronald Pandolfi
2024	J	`jnl`	Efficient Decision Trees for Tensor Regressions. CoRR Hengrui Luo, Akira Horiguchi, Li Ma
2024	J	`jnl`	Frontal Slice Approaches for Tensor Linear Systems. CoRR Hengrui Luo, Anna Ma
2024	J	`jnl`	Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization. J. Comput. Graph. Stat. Hengrui Luo, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu
2024	J	`jnl`	Multiple Closed Curve Modeling with Uncertainty Quantification for Shape Analysis. SIAM/ASA J. Uncertain. Quantification Hengrui Luo, Justin D. Strait
2024	J	`jnl`	Non-smooth Bayesian optimization in tuning scientific applications. Int. J. High Perform. Comput. Appl. Hengrui Luo, Younghyun Cho, James Weldon Demmel, Igor Kozachenko, Xiaoye S. Li, Yang Liu
2024	J	`jnl`	Ranking Perspective for Tree-based Methods with Applications to Symbolic Feature Selection. CoRR Hengrui Luo, Meng Li
2024	J	`jnl`	Spherical Rotation Dimension Reduction with Geometric Loss Functions. J. Mach. Learn. Res. Hengrui Luo, Jeremy E. Purvis, Didong Li
2024	B	`conf`	Tensor Decision Trees For High-Resolution Imaging Data. IEEE Big Data Zhihao Chen, Hengrui Luo, Suprateek Kundu, Marina Vannucci
2023	J	`jnl`	A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes. CoRR Marcus Michael Noack, Hengrui Luo, Mark D. Risser
2023	J	`jnl`	Contrastive inverse regression for dimension reduction. CoRR Sam Hawke, Hengrui Luo, Didong Li
2023	J	`jnl`	Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization. CoRR Yin-Ting Liao, Hengrui Luo, Anna Ma
2023	A	`conf`	Harnessing the Crowd for Autotuning High-Performance Computing Applications. IPDPS Younghyun Cho, James Weldon Demmel, Jacob King, Xiaoye S. Li, Yang Liu, Hengrui Luo
2023	J	`jnl`	Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software. CoRR 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
2023	J	`jnl`	Sharded Bayesian Additive Regression Trees. CoRR Hengrui Luo, Matthew T. Pratola
2023	J	`jnl`	Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems. CoRR Younghyun Cho, James Weldon Demmel, Michal Derezinski, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley J. Murray
2023	J	`jnl`	Topological Learning for Motion Data via Mixed Coordinates. CoRR Hengrui Luo, Jisu Kim, Alice Patania, Mikael Vejdemo-Johansson
2022	J	`jnl`	A Distance-Preserving Matrix Sketch. J. Comput. Graph. Stat. Leland Wilkinson, Hengrui Luo
2022	J	`jnl`	Hybrid Models for Mixed Variables in Bayesian Optimization. CoRR Hengrui Luo, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu
2022	J	`jnl`	Nonparametric Multi-shape Modeling with Uncertainty Quantification. CoRR Hengrui Luo, Justin D. Strait
2022	J	`jnl`	Sparse Additive Gaussian Process Regression. J. Mach. Learn. Res. Hengrui Luo, Giovanni Nattino, Matthew T. Pratola
2022	J	`jnl`	Spherical Rotation Dimension Reduction with Geometric Loss Functions. CoRR Hengrui Luo, Didong Li
2021	—	`conf`	Combining Geometric and Topological Information for Boundary Estimation. IEEE BigData Hengrui Luo, Justin D. Strait
2021	—	`conf`	Enhancing Autotuning Capability with a History Database. MCSoC Younghyun Cho, James Demmel, Xiaoye S. Li, Yang Liu, Hengrui Luo
2021	J	`jnl`	Non-smooth Bayesian Optimization in Tuning Problems. CoRR Hengrui Luo, James Weldon Demmel, Younghyun Cho, Xiaoye S. Li, Yang Liu
2021	—	`conf`	Topological Learning for Motion Data via Mixed Coordinates. IEEE BigData Hengrui Luo, Jisu Kim, Alice Patania, Mikael Vejdemo-Johansson
2020	J	`jnl`	A Distance-preserving Matrix Sketch. CoRR Leland Wilkinson, Hengrui Luo
2020	J	`jnl`	Generalized Penalty for Circular Coordinate Representation. CoRR Hengrui Luo, Alice Patania, Jisu Kim, Mikael Vejdemo-Johansson
2019	J	`jnl`	Combining Geometric and Topological Information in Image Segmentation. CoRR Hengrui Luo, Justin D. Strait, Abhijoy Saha