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James Demmel
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Publications
- 2025
- [j96]Younghyun Cho, James Demmel, Michal Derezinski, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley Murray
:
Surrogate-Based Autotuning for Randomized Sketching Algorithms in Regression Problems. SIAM J. Matrix Anal. Appl. 46(2): 1247-1279 (2025) - 2024
- [j95]Hengrui Luo
, Younghyun Cho
, James Weldon Demmel, Igor Kozachenko, Xiaoye S. Li
, Yang Liu
:
Non-smooth Bayesian optimization in tuning scientific applications. Int. J. High Perform. Comput. Appl. 38(6): 633-657 (2024) - [j94]Hengrui Luo
, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu
:
Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization. J. Comput. Graph. Stat. 33(3): 855-868 (2024) - 2023
- [c115]Younghyun Cho, James Weldon Demmel, Jacob King
, Xiaoye S. Li, Yang Liu, Hengrui Luo:
Harnessing the Crowd for Autotuning High-Performance Computing Applications. IPDPS 2023: 635-645 - [i50]Younghyun Cho, James Weldon Demmel, Michal Derezinski
, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley J. Murray
:
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems. CoRR abs/2308.15720 (2023) - 2022
- [i45]Hengrui Luo, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu:
Hybrid Models for Mixed Variables in Bayesian Optimization. CoRR abs/2206.01409 (2022) - 2021
- [c108]Younghyun Cho, James Demmel, Xiaoye S. Li, Yang Liu, Hengrui Luo:
Enhancing Autotuning Capability with a History Database. MCSoC 2021: 249-257 - [i41]Hengrui Luo, James Weldon Demmel, Younghyun Cho, Xiaoye S. Li, Yang Liu:
Non-smooth Bayesian Optimization in Tuning Problems. CoRR abs/2109.07563 (2021)

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