When dealing with tabular data, models based on decision
trees are a popular choice due to their high accuracy on these
data types, their ease of application, and explainability properties. However, when it comes to graph-structured data, it
is not clear how to apply them effectively, in a way that in-
corporates the topological information with the tabular data
available on the vertices of the graph. To address this challenge,
we introduce TREE-G. TREE-G modifies standard decision
trees, by introducing a novel split function that is specialized
for graph data. Not only does this split function incorporate
the node features and the topological information, but it also
uses a novel pointer mechanism that allows split nodes to
use information computed in previous splits. Therefore, the
split function adapts to the predictive task and the graph at
hand. We analyze the theoretical properties of TREE-G and
demonstrate its benefits empirically on multiple graph and
vertex prediction benchmarks. In these experiments, TREE-G
consistently outperforms other tree-based models and often
outperforms other graph-learning algorithms such as Graph
Neural Networks (GNNs) and Graph Kernels, sometimes by
large margins. Moreover, TREE-Gs models and their predic
tions can be explained and visualized.

TREE-G: Decision Trees Contesting Graph Neural Networks

Main Track - Machine Learning

technical paper

We are pleased to announce the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), which will be held in Vancouver, British Columbia at the Vancouver Convention Centre – West Building from 20-27 February, 2024.

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-24 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and a range of other activities to be announced.

We expect for AAAI-24 to be an in-person conference – one author of all accepted papers will be expected to present work in person unless there are exceptional circumstances that prevent this.<br><br><br><br>

In order to access the AAAI-24 event page you need to register [here](https://aaai.org/aaai-conference/registration/)

AAAI 2024

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. 

Maya Bechler-Speicher

1

18

SHORT BIO

Presentations

TREE-G: Decision Trees Contesting Graph Neural Networks

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES