3 papers
cs.LG2024
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…
cs.DS2023
Sublinear Time Algorithms for Several Geometric Optimization (With Outliers) Problems In Machine Learning
Hu Ding
In this paper, we study several important geometric optimization problems arising in machine learning. First, we revisit the Minimum Enclosing Ball (MEB) problem in Euclidean space…
cs.LG2023
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…