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Zheng Zhang
203 publications
Carey E. Priebe
102 publications
Yi Xu
100 publications
Lin Yang
100 publications
Jun Ma
90 publications
Chao Ma
82 publications
Yizhou Sun
80 publications
Mu Li
73 publications
George Karypis
69 publications
Sheng Wang
69 publications
Caiwen Ding
68 publications

∙ 08/02/2023

Tango: rethinking quantization for graph neural network training on GPUs

Graph Neural Networks (GNNs) are becoming increasingly popular due to th...

0 Shiyang Chen, et al. ∙

∙ 07/14/2023

DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training

Memory-based Temporal Graph Neural Networks are powerful tools in dynami...

0 Hongkuan Zhou, et al. ∙

∙ 06/05/2023

Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications

Model pre-training on large text corpora has been demonstrated effective...

0 Han Xie, et al. ∙

∙ 04/20/2023

Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs

How can we learn effective node representations on textual graphs? Graph...

0 Costas Mavromatis, et al. ∙

∙ 02/24/2023

PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction

Transparency and accountability have become major concerns for black-box...

0 Shichang Zhang, et al. ∙

∙ 01/16/2023

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks

Relational graph neural networks (RGNNs) are graph neural networks (GNNs...

0 Kun Wu, et al. ∙

∙ 09/24/2022

From Local to Global: Spectral-Inspired Graph Neural Networks

Graph Neural Networks (GNNs) are powerful deep learning methods for Non-...

16 Ningyuan Huang, et al. ∙

∙ 06/22/2022

Efficient and effective training of language and graph neural network models

Can we combine heterogenous graph structure with text to learn high-qual...

0 Vassilis N. Ioannidis, et al. ∙

∙ 06/21/2022

Nimble GNN Embedding with Tensor-Train Decomposition

This paper describes a new method for representing embedding tables of g...

0 Chunxing Yin, et al. ∙

∙ 03/28/2022

TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs

Many real world graphs contain time domain information. Temporal Graph N...

0 Hongkuan Zhou, et al. ∙

∙ 12/31/2021

Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs

Graph neural networks (GNN) have shown great success in learning from gr...

0 Da Zheng, et al. ∙

∙ 09/16/2021

Dr. Top-k: Delegate-Centric Top-k on GPUs

Recent top-k computation efforts explore the possibility of revising var...

0 Anil Gaihre, et al. ∙

∙ 06/11/2021

Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs

Graph neural networks (GNNs) are powerful tools for learning from graph ...

0 Jialin Dong, et al. ∙

∙ 05/03/2021

Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs

Graph convolutional network (GCN) based approaches have achieved signifi...

0 Saurav Manchanda, et al. ∙

∙ 01/19/2021

Learning over Families of Sets – Hypergraph Representation Learning for Higher Order Tasks

Graph representation learning has made major strides over the past decad...

0 Balasubramaniam Srinivasan, et al. ∙

∙ 10/11/2020

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs

Graph neural networks (GNN) have shown great success in learning from gr...

1 Da Zheng, et al. ∙

∙ 08/26/2020

FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems

Graph neural networks (GNNs) are gaining increasing popularity as a prom...

0 Yuwei Hu, et al. ∙

∙ 07/20/2020

PanRep: Universal node embeddings for heterogeneous graphs

Learning unsupervised node embeddings facilitates several downstream tas...

6 Vassilis N. Ioannidis, et al. ∙

∙ 07/20/2020

Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing

Predicting interactions among heterogenous graph structured data has num...

24 Vassilis N. Ioannidis, et al. ∙

∙ 04/18/2020

DGL-KE: Training Knowledge Graph Embeddings at Scale

Knowledge graphs have emerged as a key abstraction for organizing inform...

0 Da Zheng, et al. ∙

∙ 07/07/2019

Graphyti: A Semi-External Memory Graph Library for FlashGraph

Graph datasets exceed the in-memory capacity of most standalone machines...

0 Disa Mhembere, et al. ∙

∙ 02/24/2019

clusterNOR: A NUMA-Optimized Clustering Framework

Clustering algorithms are iterative and have complex data access pattern...

0 Dia Mhembere, et al. ∙

∙ 04/25/2018

Challenges Towards Deploying Data Intensive Scientific Applications on Extreme Heterogeneity Supercomputers

Shrinking transistors, which powered the advancement of computing in the...

0 Hang Liu, et al. ∙

∙ 09/05/2017

Linear Optimal Low Rank Projection for High-Dimensional Multi-Class Data

Classification of individual samples into one or more categories is crit...

0 Joshua T. Vogelstein, et al. ∙

∙ 02/03/2016

An SSD-based eigensolver for spectral analysis on billion-node graphs

Many eigensolvers such as ARPACK and Anasazi have been developed to comp...

0 Da Zheng, et al. ∙

∙ 06/24/2015

Optimize Unsynchronized Garbage Collection in an SSD Array

Solid state disks (SSDs) have advanced to outperform traditional hard dr...

0 Da Zheng, et al. ∙

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