24 citations · 62 across the 13 of their papers we have counts for
8 papers · 1 filter
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining
Xidong Wu, Zhengmian Hu, Jian Pei +1
Multi-party collaborative training, such as distributed learning and federated learning, is used to address the big data challenges. However, traditional multi-party collaborative…
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems
Xidong Wu, Zhengmian Hu, Heng Huang
The minimax optimization over Riemannian manifolds (possibly nonconvex constraints) has been actively applied to solve many problems, such as robust dimensionality reduction and de…
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems
Junyi Li, Feihu Huang, Heng Huang
Bilevel Optimization has witnessed notable progress recently with new emerging efficient algorithms. However, its application in the Federated Learning setting remains relatively u…
Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks
Yihan Wu, Aleksandar Bojchevski, Heng Huang
A lot of theoretical and empirical evidence shows that the flatter local minima tend to improve generalization. Adversarial Weight Perturbation (AWP) is an emerging technique to ef…
Faster Adaptive Federated Learning
Xidong Wu, Feihu Huang, Zhengmian Hu +1
Federated learning has attracted increasing attention with the emergence of distributed data. While extensive federated learning algorithms have been proposed for the non-convex di…
Communication-Efficient Robust Federated Learning with Noisy Labels
Junyi Li, Jian Pei, Heng Huang
Federated learning (FL) is a promising privacy-preserving machine learning paradigm over distributed located data. In FL, the data is kept locally by each user. This protects the u…
A Law of Robustness beyond Isoperimetry
Yihan Wu, Heng Huang, Hongyang Zhang
We study the robust interpolation problem of arbitrary data distributions supported on a bounded space and propose a two-fold law of robustness. Robust interpolation refers to the…
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform
Bo Liu, Chaowei Tan, Jiazhou Wang +7
In this paper, we present Fedlearn-Algo, an open-source privacy preserving machine learning platform. We use this platform to demonstrate our research and development results on pr…