24 citations · 47 across the 6 of their papers we have counts for
6 papers
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks
Runlin Lei, Zhen Wang, Yaliang Li +2
Graph Neural Networks (GNNs) have received extensive research attention for their promising performance in graph machine learning. Despite their extraordinary predictive accuracy,…
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
Zhen Wang, Weirui Kuang, Yuexiang Xie +4
The incredible development of federated learning (FL) has benefited various tasks in the domains of computer vision and natural language processing, and the existing frameworks suc…
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
Yuexiang Xie, Zhen Wang, Dawei Gao +6
Although remarkable progress has been made by existing federated learning (FL) platforms to provide infrastructures for development, these platforms may not well tackle the challen…
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data
Yuexiang Xie, Zhen Wang, Yaliang Li +6
High-order interactive features capture the correlation between different columns and thus are promising to enhance various learning tasks on ubiquitous tabular data. To automate t…
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search
Daoyuan Chen, Yaliang Li, Minghui Qiu +7
Large pre-trained language models such as BERT have shown their effectiveness in various natural language processing tasks. However, the huge parameter size makes them difficult to…
Artificial Intelligence for Prosthetics - challenge solutions
Łukasz Kidziński, Carmichael Ong, Sharada Prasanna Mohanty +47
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a giv…