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Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Graph Convolutional Neural Networks for Web-Scale Recommender Systems

6 June 2018
Rex Ying
Ruining He
Kaifeng Chen
Pong Eksombatchai
William L. Hamilton
J. Leskovec
    GNNBDL
ArXiv (abs)PDFHTML

Papers citing "Graph Convolutional Neural Networks for Web-Scale Recommender Systems"

50 / 1,342 papers shown
Link Prediction with Non-Contrastive Learning
Link Prediction with Non-Contrastive LearningInternational Conference on Learning Representations (ICLR), 2022
William Shiao
Zhichun Guo
Tong Zhao
Evangelos E. Papalexakis
Yozen Liu
Neil Shah
477
20
0
25 Nov 2022
GREAD: Graph Neural Reaction-Diffusion Networks
GREAD: Graph Neural Reaction-Diffusion NetworksInternational Conference on Machine Learning (ICML), 2022
Jeongwhan Choi
Seoyoung Hong
Noseong Park
Sung-Bae Cho
DiffMGNN
262
56
0
25 Nov 2022
Predicting Biomedical Interactions with Probabilistic Model Selection
  for Graph Neural Networks
Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks
K. Kishan
Rui Li
Paribesh Regmi
Anne R. Haake
100
1
0
22 Nov 2022
STGlow: A Flow-based Generative Framework with Dual Graphormer for
  Pedestrian Trajectory Prediction
STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory PredictionIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Rongqin Liang
Yuanman Li
Jiantao Zhou
Xia Li
358
23
0
21 Nov 2022
Directed Acyclic Graph Factorization Machines for CTR Prediction via
  Knowledge Distillation
Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge DistillationWeb Search and Data Mining (WSDM), 2022
Zhen Tian
Ting Bai
Ziyan Zhang
Zhiyuan Xu
Kangyi Lin
Ji-Rong Wen
Wayne Xin Zhao
220
27
0
21 Nov 2022
Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph
  Neural Networks via Reinforcement Learning
Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement LearningAAAI Conference on Artificial Intelligence (AAAI), 2022
Mingxuan Ju
Yujie Fan
Chuxu Zhang
Yanfang Ye
AAML
243
45
0
19 Nov 2022
EGRC-Net: Embedding-induced Graph Refinement Clustering Network
EGRC-Net: Embedding-induced Graph Refinement Clustering NetworkIEEE Transactions on Image Processing (IEEE TIP), 2022
Zhihao Peng
Hui Liu
Yuheng Jia
Xianqiang Lyu
226
12
0
19 Nov 2022
Blurring-Sharpening Process Models for Collaborative Filtering
Blurring-Sharpening Process Models for Collaborative FilteringAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022
Jeongwhan Choi
Seoyoung Hong
Noseong Park
Sung-Bae Cho
213
62
0
17 Nov 2022
Graph Filters for Signal Processing and Machine Learning on Graphs
Graph Filters for Signal Processing and Machine Learning on GraphsIEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Elvin Isufi
Fernando Gama
D. Shuman
Santiago Segarra
GNN
257
121
0
16 Nov 2022
Comprehensive Analysis of Over-smoothing in Graph Neural Networks from
  Markov Chains Perspective
Comprehensive Analysis of Over-smoothing in Graph Neural Networks from Markov Chains Perspective
Weichen Zhao
Chenguang Wang
Congying Han
Tiande Guo
191
1
0
12 Nov 2022
Self-Supervised Graph Structure Refinement for Graph Neural Networks
Self-Supervised Graph Structure Refinement for Graph Neural NetworksWeb Search and Data Mining (WSDM), 2022
Jianan Zhao
Qianlong Wen
Mingxuan Ju
Chuxu Zhang
Yanfang Ye
332
31
0
12 Nov 2022
Stable and Transferable Hyper-Graph Neural Networks
Stable and Transferable Hyper-Graph Neural Networks
Mikhail Hayhoe
Hans Riess
V. Preciado
Alejandro Ribeiro
330
2
0
11 Nov 2022
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86
  via Minibatch Sampling
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling
Md. Vasimuddin
Ramanarayan Mohanty
Sanchit Misra
Sasikanth Avancha
GNN
120
1
0
11 Nov 2022
Situating Recommender Systems in Practice: Towards Inductive Learning
  and Incremental Updates
Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates
Tobias Schnabel
Mengting Wan
Longqi Yang
HAI
159
10
0
11 Nov 2022
A Comprehensive Survey on Distributed Training of Graph Neural Networks
A Comprehensive Survey on Distributed Training of Graph Neural NetworksProceedings of the IEEE (Proc. IEEE), 2022
Haiyang Lin
Yurui Lai
Xiaochun Ye
Xiaochun Ye
Shirui Pan
Wenguang Chen
Yuan Xie
GNN
291
39
0
10 Nov 2022
TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative
  Filtering
TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering
Seoyoung Hong
Minju Jo
Seung-Uk Kook
Jaeeun Jung
Hyowon Wi
Noseong Park
Sung-Bae Cho
AI4TS
186
7
0
08 Nov 2022
Graph Contrastive Learning with Implicit Augmentations
Graph Contrastive Learning with Implicit AugmentationsNeural Networks (NN), 2022
Huidong Liang
Xingjian Du
Bilei Zhu
Zejun Ma
Ke Chen
Junbin Gao
143
39
0
07 Nov 2022
Exponentially Improving the Complexity of Simulating the
  Weisfeiler-Lehman Test with Graph Neural Networks
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2022
Anders Aamand
Justin Y. Chen
Piotr Indyk
Shyam Narayanan
R. Rubinfeld
Nicholas Schiefer
Sandeep Silwal
Tal Wagner
274
25
0
06 Nov 2022
Unlearning Graph Classifiers with Limited Data Resources
Unlearning Graph Classifiers with Limited Data ResourcesThe Web Conference (WWW), 2022
Chao Pan
Eli Chien
O. Milenkovic
MU
260
39
0
06 Nov 2022
Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph
  Node Classifiers
Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph Node Classifiers
Haris Mansoor
Sarwan Ali
Shafiq Alam
Muhammad Asad Khan
U. Hassan
Imdadullah Khan
FaML
173
5
0
01 Nov 2022
Track2Vec: fairness music recommendation with a GPU-free
  customizable-driven framework
Track2Vec: fairness music recommendation with a GPU-free customizable-driven framework
Wei Du
Wei-Yao Wang
Chao-Han Huck Yang
152
0
0
29 Oct 2022
Training Graph Neural Networks on Growing Stochastic Graphs
Training Graph Neural Networks on Growing Stochastic GraphsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
J. Cerviño
Luana Ruiz
Alejandro Ribeiro
GNN
229
8
0
27 Oct 2022
TuneUp: A Simple Improved Training Strategy for Graph Neural Networks
TuneUp: A Simple Improved Training Strategy for Graph Neural Networks
Weihua Hu
Kaidi Cao
Kexin Huang
E-Wen Huang
Karthik Subbian
Kenji Kawaguchi
J. Leskovec
181
0
0
26 Oct 2022
Network Aware Compute and Memory Allocation in Optically Composable Data
  Centres with Deep Reinforcement Learning and Graph Neural Networks
Network Aware Compute and Memory Allocation in Optically Composable Data Centres with Deep Reinforcement Learning and Graph Neural NetworksJournal of Optical Communications and Networking (JOCN), 2022
Zacharaya Shabka
G. Zervas
GNN
125
5
0
26 Oct 2022
Layer-Neighbor Sampling -- Defusing Neighborhood Explosion in GNNs
Layer-Neighbor Sampling -- Defusing Neighborhood Explosion in GNNsNeural Information Processing Systems (NeurIPS), 2022
M. F. Balin
Ümit V. Çatalyürek
181
28
0
24 Oct 2022
Binary Graph Convolutional Network with Capacity Exploration
Binary Graph Convolutional Network with Capacity ExplorationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Junfu Wang
Yuanfang Guo
Liang Yang
Yun-an Wang
GNN
230
11
0
24 Oct 2022
Graph Few-shot Learning with Task-specific Structures
Graph Few-shot Learning with Task-specific StructuresNeural Information Processing Systems (NeurIPS), 2022
Song Wang
Chen Chen
Jundong Li
138
24
0
21 Oct 2022
A Survey on Graph Counterfactual Explanations: Definitions, Methods,
  Evaluation, and Research Challenges
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research ChallengesACM Computing Surveys (ACM CSUR), 2022
Mario Alfonso Prado-Romero
Bardh Prenkaj
Giovanni Stilo
F. Giannotti
CML
285
42
0
21 Oct 2022
Global Counterfactual Explainer for Graph Neural Networks
Global Counterfactual Explainer for Graph Neural NetworksWeb Search and Data Mining (WSDM), 2022
Mert Kosan
Zexi Huang
Sourav Medya
Jignesh M. Patel
Ambuj K. Singh
225
61
0
21 Oct 2022
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse
  Computations
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse ComputationsInternational Conference on Machine Learning (ICML), 2022
Zirui Liu
Sheng-Wei Chen
Kaixiong Zhou
Daochen Zha
Xiao Huang
Helen Zhou
321
22
0
19 Oct 2022
On Classification Thresholds for Graph Attention with Edge Features
On Classification Thresholds for Graph Attention with Edge Features
Kimon Fountoulakis
Dake He
Silvio Lattanzi
Bryan Perozzi
Anton Tsitsulin
Shenghao Yang
GNN
297
6
0
18 Oct 2022
Code Recommendation for Open Source Software Developers
Code Recommendation for Open Source Software DevelopersThe Web Conference (WWW), 2022
Yiqiao Jin
Yunsheng Bai
Yanqiao Zhu
Luke Huan
Wei Wang
263
28
0
15 Oct 2022
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great AgainNeural Information Processing Systems (NeurIPS), 2022
Ajay Jaiswal
Peihao Wang
Tianlong Chen
Justin F. Rousseau
Ying Ding
Zinan Lin
192
15
0
14 Oct 2022
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and
  Rethinking
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and RethinkingNeural Information Processing Systems (NeurIPS), 2022
Keyu Duan
Zirui Liu
Peihao Wang
Wenqing Zheng
Kaixiong Zhou
Tianlong Chen
Helen Zhou
Zinan Lin
GNN
254
77
0
14 Oct 2022
Linkless Link Prediction via Relational Distillation
Linkless Link Prediction via Relational DistillationInternational Conference on Machine Learning (ICML), 2022
Zhichun Guo
William Shiao
Shichang Zhang
Yozen Liu
Nitesh Chawla
Neil Shah
Tong Zhao
355
54
0
11 Oct 2022
Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining
Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining
Jaemin Yoo
Meng-Chieh Lee
Shubhranshu Shekhar
Christos Faloutsos
316
11
0
08 Oct 2022
Learning the Network of Graphs for Graph Neural Networks
Learning the Network of Graphs for Graph Neural Networks
Yixiang Shan
Jielong Yang
Xing Liu
Yixing Gao
Hechang Chen
Shiwei Gan
174
0
0
08 Oct 2022
Empowering Graph Representation Learning with Test-Time Graph
  Transformation
Empowering Graph Representation Learning with Test-Time Graph TransformationInternational Conference on Learning Representations (ICLR), 2022
Wei Jin
Tong Zhao
Jiayu Ding
Yozen Liu
Shucheng Zhou
Neil Shah
OOD
424
78
0
07 Oct 2022
Graph Classification via Discriminative Edge Feature Learning
Graph Classification via Discriminative Edge Feature LearningPattern Recognition (Pattern Recogn.), 2022
Yang Yi
Xuequan Lu
Shang Gao
A. Robles-Kelly
Yuejie Zhang
GNN
228
12
0
05 Oct 2022
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task
  Generalization
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task GeneralizationInternational Conference on Learning Representations (ICLR), 2022
Mingxuan Ju
Tong Zhao
Qianlong Wen
Wenhao Yu
Neil Shah
Yanfang Ye
Chuxu Zhang
SSL
402
47
0
05 Oct 2022
Towards Prototype-Based Self-Explainable Graph Neural Network
Towards Prototype-Based Self-Explainable Graph Neural NetworkACM Transactions on Knowledge Discovery from Data (TKDD), 2022
Enyan Dai
Suhang Wang
203
18
0
05 Oct 2022
Learning from the Dark: Boosting Graph Convolutional Neural Networks
  with Diverse Negative Samples
Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative SamplesAAAI Conference on Artificial Intelligence (AAAI), 2022
Wei Duan
Junyu Xuan
Maoying Qiao
Jie Lu
SSL
201
52
0
03 Oct 2022
Gradient Gating for Deep Multi-Rate Learning on Graphs
Gradient Gating for Deep Multi-Rate Learning on GraphsInternational Conference on Learning Representations (ICLR), 2022
T. Konstantin Rusch
B. Chamberlain
Michael W. Mahoney
Michael M. Bronstein
Siddhartha Mishra
402
71
0
02 Oct 2022
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP
  Initialization
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP InitializationInternational Conference on Learning Representations (ICLR), 2022
Xiaotian Han
Tong Zhao
Yozen Liu
Helen Zhou
Neil Shah
GNN
536
46
0
30 Sep 2022
Contrastive Graph Few-Shot Learning
Contrastive Graph Few-Shot Learning
Chunhui Zhang
Hongfu Liu
Jundong Li
Yanfang Ye
Chuxu Zhang
247
1
0
30 Sep 2022
Efficient Graph based Recommender System with Weighted Averaging of
  Messages
Efficient Graph based Recommender System with Weighted Averaging of MessagesInternational Conference on AI-ML-Systems (ICA), 2022
Faizan Ahemad
65
1
0
30 Sep 2022
How Powerful is Implicit Denoising in Graph Neural Networks
How Powerful is Implicit Denoising in Graph Neural Networks
Songtao Liu
Rex Ying
Hanze Dong
Lu Lin
Jinghui Chen
Di Wu
GNNAI4CE
267
3
0
29 Sep 2022
LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy
  Physics
LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy PhysicsACM Transactions on Embedded Computing Systems (TECS), 2022
Zhiqiang Que
Hongxiang Fan
Marcus Loo
He Li
Michaela Blott
M. Pierini
A. Tapper
Wayne Luk
GNN
545
24
0
28 Sep 2022
Flattened Graph Convolutional Networks For Recommendation
Flattened Graph Convolutional Networks For Recommendation
Yue Xu
Hao Chen
Zengde Deng
Yuanchen Bei
Feiran Huang
BDLGNN
137
1
0
25 Sep 2022
Rethinking the compositionality of point clouds through regularization
  in the hyperbolic space
Rethinking the compositionality of point clouds through regularization in the hyperbolic spaceNeural Information Processing Systems (NeurIPS), 2022
Antonio Montanaro
D. Valsesia
E. Magli
3DPC
210
40
0
21 Sep 2022
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