no code implementations • 17 Dec 2023 • Liyun Zeng, Hao Helen Zhang
The binary class probability is then estimated either by the $\ell^2$-norm regularized wSVMs framework with selected variables or by elastic net regularized wSVMs directly.
no code implementations • 15 Nov 2023 • Liyun Zeng, Hao Helen Zhang
Nonetheless, deep learning-based image classification methods, including CNN, face challenges in estimating class probabilities without proper model calibration.
no code implementations • 21 Feb 2023 • Keaton Hamm, Zhaoying Lu, Wenbo Ouyang, Hao Helen Zhang
To improve the standard Nystr\"{o}m approximation, ensemble Nystr\"{o}m algorithms compute a mixture of Nystr\"{o}m approximations which are generated independently based on column resampling.
1 code implementation • 25 May 2022 • Liyun Zeng, Hao Helen Zhang
In particular, the baseline learning has optimal computational complexity in the sense that it is linear in $K$.
1 code implementation • 5 May 2022 • MohammadReza Ebrahimi, Yidong Chai, Hao Helen Zhang, Hsinchun Chen
This incentivizes developing domain adaptation methods that leverage the knowledge in known domains (source) and adapt to new domains (target) with a different probability distribution.
no code implementations • 4 May 2021 • Chanwoo Lee, Lexin Li, Hao Helen Zhang, Miaoyan Wang
Trace regression is a widely used method to model effects of matrix predictors and has shown great success in matrix learning.
no code implementations • 5 Jun 2019 • Xin Wang, Zhengyuan Zhu, Hao Helen Zhang
Spatial regression is widely used for modeling the relationship between a dependent variable and explanatory covariates.
Methodology