11 citations · 35 across the 24 of their papers we have counts for
6 papers · 1 filter
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…
Coresets for Relational Data and The Applications
Jiaxiang Chen, Qingyuan Yang, Ruomin Huang +1
A coreset is a small set that can approximately preserve the structure of the original input data set. Therefore we can run our algorithm on a coreset so as to reduce the total com…
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…
Is Simple Uniform Sampling Effective for Center-Based Clustering with Outliers: When and Why?
Jiawei Huang, Wenjie Liu, Hu Ding
Real-world datasets often contain outliers, and the presence of outliers can make the clustering problems to be much more challenging. In this paper, we propose a simple uniform sa…
Defending SVMs against Poisoning Attacks: the Hardness and DBSCAN Approach
Hu Ding, Fan Yang, Jiawei Huang
Adversarial machine learning has attracted a great amount of attention in recent years. In a poisoning attack, the adversary can inject a small number of specially crafted samples…
On Geometric Alignment in Low Doubling Dimension
Hu Ding, Mingquan Ye
In real-world, many problems can be formulated as the alignment between two geometric patterns. Previously, a great amount of research focus on the alignment of 2D or 3D patterns,…