Search to aggregate neighborhood for graph neural network

04/14/2021
by   Huan Zhao, et al.
0

Recent years have witnessed the popularity and success of graph neural networks (GNN) in various scenarios. To obtain data-specific GNN architectures, researchers turn to neural architecture search (NAS), which has made impressive success in discovering effective architectures in convolutional neural networks. However, it is non-trivial to apply NAS approaches to GNN due to challenges in search space design and the expensive searching cost of existing NAS methods. In this work, to obtain the data-specific GNN architectures and address the computational challenges facing by NAS approaches, we propose a framework, which tries to Search to Aggregate NEighborhood (SANE), to automatically design data-specific GNN architectures. By designing a novel and expressive search space, we propose a differentiable search algorithm, which is more efficient than previous reinforcement learning based methods. Experimental results on four tasks and seven real-world datasets demonstrate the superiority of SANE compared to existing GNN models and NAS approaches in terms of effectiveness and efficiency. (Code is available at: https://github.com/AutoML-4Paradigm/SANE).

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/26/2020

Simplifying Architecture Search for Graph Neural Network

Recent years have witnessed the popularity of Graph Neural Networks (GNN...
research
10/30/2022

Search to Pass Messages for Temporal Knowledge Graph Completion

Completing missing facts is a fundamental task for temporal knowledge gr...
research
08/30/2023

Efficient and Explainable Graph Neural Architecture Search via Monte-Carlo Tree Search

Graph neural networks (GNNs) are powerful tools for performing data scie...
research
09/21/2021

Search For Deep Graph Neural Networks

Current GNN-oriented NAS methods focus on the search for different layer...
research
02/23/2023

Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs

Graph neural architecture search (NAS) has gained popularity in automati...
research
09/21/2020

Evolutionary Architecture Search for Graph Neural Networks

Automated machine learning (AutoML) has seen a resurgence in interest wi...
research
03/14/2023

AutoTransfer: AutoML with Knowledge Transfer – An Application to Graph Neural Networks

AutoML has demonstrated remarkable success in finding an effective neura...

Please sign up or login with your details

Forgot password? Click here to reset