2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Randomized Greedy Algorithms and Composable Coreset for k-Center Clustering with Outliers
Hu Ding, Ruomin Huang, Kai Liu +2
In this paper, we study the problem of {\em -center clustering with outliers}. The problem has many important applications in real world, but the presence of outliers can signif…
cs.LG2021★ 2 cited
Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems
Zixiu Wang, Yiwen Guo, Hu Ding
In many machine learning tasks, a common approach for dealing with large-scale data is to build a small summary, {\em e.g.,} coreset, that can efficiently represent the original in…
cs.CG2020
Layered Sampling for Robust Optimization Problems
Hu Ding, Zixiu Wang
In real world, our datasets often contain outliers. Moreover, the outliers can seriously affect the final machine learning result. Most existing algorithms for handling outliers ta…