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On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for
  Language Processing

On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing

6 October 2022
Zeming Dong
Qiang Hu
Zhenya Zhang
Yuejun Guo
Maxime Cordy
Mike Papadakis
Yves Le Traon
Jianjun Zhao
ArXivPDFHTML

Papers citing "On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing"

26 / 26 papers shown
Title
MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentation
MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentation
Zeming Dong
Qiang Hu
Yuejun Guo
Maxime Cordy
Mike Papadakis
Zhenya Zhang
Yves Le Traon
Jianjun Zhao
48
8
0
06 Oct 2022
Understanding Pooling in Graph Neural Networks
Understanding Pooling in Graph Neural Networks
Daniele Grattarola
Daniele Zambon
F. Bianchi
Cesare Alippi
GNN
FAtt
AI4CE
376
93
0
11 Oct 2021
SSMix: Saliency-Based Span Mixup for Text Classification
SSMix: Saliency-Based Span Mixup for Text Classification
Soyoung Yoon
Gyuwan Kim
Kyumin Park
46
71
0
15 Jun 2021
Self-Supervised Bug Detection and Repair
Self-Supervised Bug Detection and Repair
Miltiadis Allamanis
Henry Jackson-Flux
Marc Brockschmidt
66
105
0
26 May 2021
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of
  Coding Tasks
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks
Ruchi Puri
David S. Kung
G. Janssen
Wei Zhang
Giacomo Domeniconi
...
Saurabh Pujar
Shyam Ramji
Ulrich Finkler
Susan Malaika
Frederick Reiss
72
237
0
25 May 2021
An Empirical Study of Contextual Data Augmentation for Japanese Zero
  Anaphora Resolution
An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution
Ryuto Konno
Yuichiroh Matsubayashi
Shun Kiyono
Hiroki Ouchi
Ryo Takahashi
Kentaro Inui
38
7
0
02 Nov 2020
How Does Mixup Help With Robustness and Generalization?
How Does Mixup Help With Robustness and Generalization?
Linjun Zhang
Zhun Deng
Kenji Kawaguchi
Amirata Ghorbani
James Zou
AAML
73
250
0
09 Oct 2020
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Wenzheng Feng
Jie Zhang
Yuxiao Dong
Yu Han
Huanbo Luan
Qian Xu
Qiang Yang
Evgeny Kharlamov
Jie Tang
85
393
0
22 May 2020
MixText: Linguistically-Informed Interpolation of Hidden Space for
  Semi-Supervised Text Classification
MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification
Jiaao Chen
Zichao Yang
Diyi Yang
VLM
80
363
0
25 Apr 2020
Every Document Owns Its Structure: Inductive Text Classification via
  Graph Neural Networks
Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks
Yufeng Zhang
Xueli Yu
Zeyu Cui
Shu Wu
Zhongzheng Wen
Liang Wang
GNN
67
287
0
22 Apr 2020
Detecting Code Clones with Graph Neural Networkand Flow-Augmented
  Abstract Syntax Tree
Detecting Code Clones with Graph Neural Networkand Flow-Augmented Abstract Syntax Tree
Wenhan Wang
Ge Li
Bo Ma
Xin Xia
Zhi Jin
GNN
46
254
0
20 Feb 2020
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph
  Representations
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ekagra Ranjan
Soumya Sanyal
Partha P. Talukdar
GNN
148
331
0
18 Nov 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node
  Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
Yu Rong
Wenbing Huang
Tingyang Xu
Junzhou Huang
104
1,334
0
25 Jul 2019
CutMix: Regularization Strategy to Train Strong Classifiers with
  Localizable Features
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Sangdoo Yun
Dongyoon Han
Seong Joon Oh
Sanghyuk Chun
Junsuk Choe
Y. Yoo
OOD
604
4,766
0
13 May 2019
Graph U-Nets
Graph U-Nets
Hongyang Gao
Shuiwang Ji
AI4CE
SSL
SSeg
GNN
110
1,084
0
11 May 2019
Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
Jia Li
Yu Rong
Hong Cheng
Helen Meng
Wen-bing Huang
Junzhou Huang
35
150
0
10 Apr 2019
Fast Graph Representation Learning with PyTorch Geometric
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey
J. E. Lenssen
3DH
GNN
3DPC
204
4,334
0
06 Mar 2019
A Comprehensive Survey on Graph Neural Networks
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu
Shirui Pan
Fengwen Chen
Guodong Long
Chengqi Zhang
Philip S. Yu
FaML
GNN
AI4TS
AI4CE
644
8,496
0
03 Jan 2019
Towards Sparse Hierarchical Graph Classifiers
Towards Sparse Hierarchical Graph Classifiers
Cătălina Cangea
Petar Velickovic
Nikola Jovanović
Thomas Kipf
Pietro Lio
GNN
170
258
0
03 Nov 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
220
7,623
0
01 Oct 2018
Learning to Represent Programs with Graphs
Learning to Represent Programs with Graphs
Miltiadis Allamanis
Marc Brockschmidt
Mahmoud Khademi
GNN
NAI
117
799
0
01 Nov 2017
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
271
9,743
0
25 Oct 2017
A Survey of Machine Learning for Big Code and Naturalness
A Survey of Machine Learning for Big Code and Naturalness
Miltiadis Allamanis
Earl T. Barr
Premkumar T. Devanbu
Charles Sutton
108
854
0
18 Sep 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
458
15,179
0
07 Jun 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
508
7,431
0
04 Apr 2017
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
511
27,263
0
01 Sep 2014
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