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∙ 01/07/2023

Sublinear Time Algorithms for Several Geometric Optimization (With Outliers) Problems In Machine Learning

In this paper, we study several important geometric optimization problem...

0 Hu Ding, et al. ∙

∙ 01/07/2023

Randomized Greedy Algorithms and Composable Coreset for k-Center Clustering with Outliers

In this paper, we study the problem of k-center clustering with outliers...

0 Hu Ding, et al. ∙

∙ 10/09/2022

Coresets for Wasserstein Distributionally Robust Optimization Problems

Wasserstein distributionally robust optimization () is a popular model t...

0 Ruomin Huang, et al. ∙

∙ 10/09/2022

Coresets for Relational Data and The Applications

A coreset is a small set that can approximately preserve the structure o...

0 Jiaxiang Chen, et al. ∙

∙ 09/07/2022

A Data-dependent Approach for High Dimensional (Robust) Wasserstein Alignment

Many real-world problems can be formulated as the alignment between two ...

0 Hu Ding, et al. ∙

∙ 12/05/2021

A Novel Sequential Coreset Method for Gradient Descent Algorithms

A wide range of optimization problems arising in machine learning can be...

0 Jiawei Huang, et al. ∙

∙ 06/30/2021

Robust Coreset for Continuous-and-Bounded Learning (with Outliers)

In this big data era, we often confront large-scale data in many machine...

0 Zixiu Wang, et al. ∙

∙ 02/28/2021

Is Simple Uniform Sampling Efficient for Center-Based Clustering With Outliers: When and Why?

Clustering has many important applications in computer science, but real...

0 Hu Ding, et al. ∙

∙ 11/16/2020

Gradient Episodic Memory with a Soft Constraint for Continual Learning

Catastrophic forgetting in continual learning is a common destructive ph...

0 Guannan Hu, et al. ∙

∙ 06/14/2020

Defending SVMs against Poisoning Attacks: the Hardness and DBSCAN Approach

Adversarial machine learning has attracted a great amount of attention i...

60 Hu Ding, et al. ∙

∙ 04/20/2020

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

Many real-world problems can be formulated as geometric optimization pro...

0 Hu Ding, et al. ∙

∙ 02/27/2020

On Metric DBSCAN with Low Doubling Dimension

The density based clustering method Density-Based Spatial Clustering of ...

0 Hu Ding, et al. ∙

∙ 02/27/2020

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

In this paper, we consider the following query problem: given two weight...

0 Hu Ding, et al. ∙

∙ 02/27/2020

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

In this paper, we consider the following query problem: given two weight...

0 Hu Ding, et al. ∙

∙ 02/27/2020

The Effectiveness of Johnson-Lindenstrauss Transform for High Dimensional Optimization with Outliers

Johnson-Lindenstrauss (JL) Transform is one of the most popular methods ...

0 Hu Ding, et al. ∙

∙ 02/27/2020

Layered Sampling for Robust Optimization Problems

In real world, our datasets often contain outliers. Moreover, the outlie...

0 Hu Ding, et al. ∙

∙ 05/24/2019

A Practical Framework for Solving Center-Based Clustering with Outliers

Clustering has many important applications in computer science, but real...

0 Hu Ding, et al. ∙

∙ 04/08/2019

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

In this paper, we revisit the Minimum Enclosing Ball (MEB) problem and i...

0 Hu Ding, et al. ∙

∙ 04/08/2019

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

In this paper, we revisit the Minimum Enclosing Ball (MEB) problem and i...

0 Hu Ding, et al. ∙

∙ 01/24/2019

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

We study the problem of k-center clustering with outliers in arbitrary m...

0 Hu Ding, et al. ∙

∙ 01/24/2019

Greedy Strategy Works for Clustering with Outliers and Coresets Construction

We study the problems of clustering with outliers in high dimension. Tho...

0 Hu Ding, et al. ∙

∙ 11/19/2018

On Geometric Alignment in Low Doubling Dimension

In real-world, many problems can be formulated as the alignment between ...

0 Hu Ding, et al. ∙

∙ 10/02/2018

A Unified Framework for Clustering Constrained Data without Locality Property

In this paper, we consider a class of constrained clustering problems of...

0 Hu Ding, et al. ∙

∙ 09/04/2018

Faster Balanced Clusterings in High Dimension

The problem of constrained clustering has attracted significant attentio...

0 Hu Ding, et al. ∙

∙ 04/25/2018

On Geometric Prototype And Applications

In this paper, we propose to study a new geometric optimization problem ...

0 Hu Ding, et al. ∙

∙ 04/25/2018

Bi-criteria Approximation Algorithms for Minimum Enclosing Ball and k-Center Clustering with Outliers

Motivated by the arising realistic issues in big data, the problem of Mi...

0 Hu Ding, et al. ∙

∙ 04/25/2018

Solving Minimum Enclosing Ball with Outliers: Algorithm, Implementation, and Application

Motivated by the arising realistic issues in big data, the problem of Mi...

0 Hu Ding, et al. ∙

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