4 citations · 12 across the 7 of their papers we have counts for
7 papers
An Effective Dynamic Gradient Calibration Method for Continual Learning
Weichen Lin, Jiaxiang Chen, Ruomin Huang +1
Continual learning (CL) is a fundamental topic in machine learning, where the goal is to train a model with continuously incoming data and tasks. Due to the memory limit, we cannot…
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…
Coresets for Wasserstein Distributionally Robust Optimization Problems
Ruomin Huang, Jiawei Huang, Wenjie Liu +1
Wasserstein distributionally robust optimization (\textsf{WDRO}) is a popular model to enhance the robustness of machine learning with ambiguous data. However, the complexity of \t…
A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang, Ruomin Huang, Wenjie Liu +2
A wide range of optimization problems arising in machine learning can be solved by gradient descent algorithms, and a central question in this area is how to efficiently compress a…
Learning optimal multigrid smoothers via neural networks
Ru Huang, Ruipeng Li, Yuanzhe Xi
Multigrid methods are one of the most efficient techniques for solving linear systems arising from Partial Differential Equations (PDEs) and graph Laplacians from machine learning…
Generating a Doppelganger Graph: Resembling but Distinct
Yuliang Ji, Ru Huang, Jie Chen +1
Deep generative models, since their inception, have become increasingly more capable of generating novel and perceptually realistic signals (e.g., images and sound waves). With the…