13 citations · 37 across the 4 of their papers we have counts for
5 papers
Learning to Rank Normalized Entropy Curves with Differentiable Window Transformation
Hanyang Liu, Shuai Yang, Feng Qi +1
Recent automated machine learning systems often use learning curves ranking models to inform decisions about when to stop unpromising trials and identify better model configuration…
Does SLOPE outperform bridge regression?
Shuaiwen Wang, Haolei Weng, Arian Maleki
A recently proposed SLOPE estimator (arXiv:1407.3824) has been shown to adaptively achieve the minimax estimation rate under high-dimensional sparse linear regression mode…
Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems
Shuaiwen Wang, Wenda Zhou, Arian Maleki +2
Consider the following class of learning schemes: \begin{equation} \label{eq:main-problem1} \hat{\boldsymbolβ} := \underset{\boldsymbolβ \in \mathcal{C}}{\arg\min} \;\sum_{j=1}^n \…
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Shuaiwen Wang, Wenda Zhou, Haihao Lu +2
Consider the following class of learning schemes: $$\hat{\boldsymbolβ} := \arg\min_{\boldsymbolβ}\;\sum_{j=1}^n \ell(\boldsymbol{x}_j^\top\boldsymbolβ; y_j) + λR(\boldsymbolβ),\qqu…
Which bridge estimator is optimal for variable selection?
Shuaiwen Wang, Haolei Weng, Arian Maleki
We study the problem of variable selection for linear models under the high-dimensional asymptotic setting, where the number of observations grows at the same rate as the numbe…