6 citations · 15 across the 8 of their papers we have counts for
13 papers
Coresets for Vertical Federated Learning: Regularized Linear Regression and -Means Clustering
Lingxiao Huang, Zhize Li, Jialin Sun +1
Vertical federated learning (VFL), where data features are stored in multiple parties distributively, is an important area in machine learning. However, the communication complexit…
Efficient Submodular Optimization under Noise: Local Search is Robust
Lingxiao Huang, Yuyi Wang, Chunxue Yang +1
The problem of monotone submodular maximization has been studied extensively due to its wide range of applications. However, there are cases where one can only access the objective…
Near-optimal Coresets for Robust Clustering
Lingxiao Huang, Shaofeng H. -C. Jiang, Jianing Lou +1
We consider robust clustering problems in , specifically -clustering problems (e.g., -Median and -Means with outliers, where the cost for a given center…
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…
Coresets for Time Series Clustering
Lingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi
We study the problem of constructing coresets for clustering problems with time series data. This problem has gained importance across many fields including biology, medicine, and…
Coresets for Regressions with Panel Data
Lingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi
This paper introduces the problem of coresets for regression problems to panel data settings. We first define coresets for several variants of regression problems with panel data a…