activity
20172020
most citedGreedy Strategy Works for -Center Clustering with Outliers and Coreset Construction

11 citations · 15 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CG2020

A Sub-linear Time Framework for Geometric Optimization with Outliers in High Dimensions

Hu Ding

Many real-world problems can be formulated as geometric optimization problems in high dimensions, especially in the fields of machine learning and data mining. Moreover, we often n…

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…

cs.CG2020

A Data-Dependent Algorithm for Querying Earth Mover's Distance with Low Doubling Dimensions

Hu Ding, Tan Chen, Fan Yang +1

In this paper, we consider the following query problem: given two weighted point sets and in the Euclidean space , we want to quickly determine that whether t…

cs.DS2019

The Effectiveness of Uniform Sampling for Center-Based Clustering with Outliers

Hu Ding, Jiawei Huang, Haikuo Yu

Clustering has many important applications in computer science, but real-world datasets often contain outliers. Moreover, the presence of outliers can make the clustering problems…

cs.CG2019

Minimum Enclosing Ball Revisited: Stability and Sub-linear Time Algorithms

Hu Ding

In this paper, we revisit the Minimum Enclosing Ball (MEB) problem and its robust version, MEB with outliers, in Euclidean space . Though the problem has been extensi…

cs.CG201911 cited

Greedy Strategy Works for -Center Clustering with Outliers and Coreset Construction

Hu Ding, Haikuo Yu, Zixiu Wang

We study the problem of -center clustering with outliers in arbitrary metrics and Euclidean space. Though a number of methods have been developed in the past decades, it is stil…