information bottleneck

Alimama Tech

Nov 22, 2023 · Artificial Intelligence

Robust Link Prediction under Bilateral Edge Noise via Robust Graph Information Bottleneck (RGIB)

The paper introduces Robust Graph Information Bottleneck (RGIB), a framework that jointly mitigates bilateral edge noise in link prediction by decoupling topology, label, and representation information, with two variants (RGIB‑SSL and RGIB‑REP) that achieve up to 12.9% AUC gains on benchmarks and have already boosted click‑through‑rate robustness and revenue in Alibaba’s advertising system.

Graph Neural NetworksRGIBbilateral noise

0 likes · 13 min read

Robust Link Prediction under Bilateral Edge Noise via Robust Graph Information Bottleneck (RGIB)

DataFunSummit

Jan 8, 2022 · Artificial Intelligence

Graph Information Bottleneck and AD‑GCL: Enhancing Graph Representation Learning and Robustness

This article introduces graph representation learning, explains the Graph Information Bottleneck (GIB) framework for obtaining robust graph embeddings, and presents AD‑GCL, a contrastive learning method that leverages GIB principles to improve graph neural network performance without requiring task labels.

Graph Neural NetworksGraph Representationcontrastive learning

0 likes · 15 min read

Graph Information Bottleneck and AD‑GCL: Enhancing Graph Representation Learning and Robustness

DataFunTalk

Dec 11, 2021 · Artificial Intelligence

Graph Information Bottleneck (GIB) and AD‑GCL: Enhancing Graph Representation Learning and Robustness

This article introduces graph representation learning, explains the Graph Information Bottleneck (GIB) framework for obtaining robust graph embeddings, and presents AD‑GCL, a contrastive learning method that leverages GIB principles to improve robustness and performance without requiring task labels.

Graph Neural Networkscontrastive learninggraph augmentation

0 likes · 16 min read

Graph Information Bottleneck (GIB) and AD‑GCL: Enhancing Graph Representation Learning and Robustness