most citedData-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model Market

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024

One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity

Naibo Wang, Yuchen Deng, Wenjie Feng +3

Traditional federated learning mainly focuses on parallel settings (PFL), which can suffer significant communication and computation costs. In contrast, one-shot and sequential fed…

cs.LG2023

Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering

Mingqi Yang, Wenjie Feng, Yanming Shen +1

Proposing an effective and flexible matrix to represent a graph is a fundamental challenge that has been explored from multiple perspectives, e.g., filtering in Graph Fourier Trans…

cs.LG2023★ 2 cited

Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model Market

Naibo Wang, Wenjie Feng, Fusheng Liu +2

The emerging availability of trained machine learning models has put forward the novel concept of Machine Learning Model Market in which one can harness the collective intelligence…