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20112023
most citedAdversarial Graph Augmentation to Improve Graph Contrastive Learning

142 citations · 334 across the 19 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.IR2023★ 11 cited

Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies

Chirag Shah, Ryen W. White, Reid Andersen +13

Log data can reveal valuable information about how users interact with Web search services, what they want, and how satisfied they are. However, analyzing user intents in log data…

cs.IR2023★ 2 cited

Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem

Jiayi Liu, Jennifer Neville

Email platforms need to generate personalized rankings of emails that satisfy user preferences, which may vary over time. We approach this as a recommendation problem based on thre…

cs.SI2023★ 29 cited

DYMOND: DYnamic MOtif-NoDes Network Generative Model

Giselle Zeno, Timothy La Fond, Jennifer Neville

Motifs, which have been established as building blocks for network structure, move beyond pair-wise connections to capture longer-range correlations in connections and activity. In…

cs.LG2023★ 4 cited

Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness

Hogun Park, Jennifer Neville

Node representation learning in a network is an important machine learning technique for encoding relational information in a continuous vector space while preserving the inherent…

cs.LG2023

Creating generalizable downstream graph models with random projections

Anton Amirov, Chris Quirk, Jennifer Neville

We investigate graph representation learning approaches that enable models to generalize across graphs: given a model trained using the representations from one graph, our goal is…