no code implementations • 30 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.
1 code implementation • 3 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.
1 code implementation • 15 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.
no code implementations • 15 Aug 2019 • Wissam M. Sid-Lakhdar, Mohsen Mahmoudi Aznaveh, Xiaoye S. Li, James W. Demmel
Multitask learning and transfer learning have proven to be useful in the field of machine learning when additional knowledge is available to help a prediction task.