11 citations · 35 across the 24 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…
The Effectiveness of Johnson-Lindenstrauss Transform for High Dimensional Optimization With Adversarial Outliers, and the Recovery
Hu Ding, Ruizhe Qin, Jiawei Huang
In this paper, we consider robust optimization problems in high dimensions. Because a real-world dataset may contain significant noise or even specially crafted samples from some a…