1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Locally Adaptive and Differentiable Regression
Mingxuan Han, Varun Shankar, Jeff M Phillips +1
Over-parameterized models like deep nets and random forests have become very popular in machine learning. However, the natural goals of continuity and differentiability, common in…
stat.ML2023
The ART of Transfer Learning: An Adaptive and Robust Pipeline
Boxiang Wang, Yunan Wu, Chenglong Ye
Transfer learning is an essential tool for improving the performance of primary tasks by leveraging information from auxiliary data resources. In this work, we propose Adaptive Rob…
stat.ME2016★ 1 cited
Sparsity Oriented Importance Learning for High-dimensional Linear Regression
Chenglong Ye, Yi Yang, Yuhong Yang
With now well-recognized non-negligible model selection uncertainty, data analysts should no longer be satisfied with the output of a single final model from a model selection proc…