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BloomGML: Graph Machine Learning through the Lens of Bilevel
  Optimization

BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization

7 March 2024
Amber Yijia Zheng
Tong He
Yixuan Qiu
Minjie Wang
David Wipf
ArXivPDFHTML

Papers citing "BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization"

5 / 5 papers shown
Title
IMMA: Immunizing text-to-image Models against Malicious Adaptation
IMMA: Immunizing text-to-image Models against Malicious Adaptation
Yijia Zheng
Raymond A. Yeh
17
8
0
30 Nov 2023
How Powerful are Spectral Graph Neural Networks
How Powerful are Spectral Graph Neural Networks
Xiyuan Wang
Muhan Zhang
70
175
0
23 May 2022
Why Propagate Alone? Parallel Use of Labels and Features on Graphs
Why Propagate Alone? Parallel Use of Labels and Features on Graphs
Yangkun Wang
Jiarui Jin
Weinan Zhang
Yongyi Yang
Jiuhai Chen
Quan Gan
Yong Yu
Zheng-Wei Zhang
Zengfeng Huang
David Wipf
AAML
50
12
0
14 Oct 2021
Beyond Low-frequency Information in Graph Convolutional Networks
Beyond Low-frequency Information in Graph Convolutional Networks
Deyu Bo
Xiao Wang
C. Shi
Huawei Shen
GNN
87
554
0
04 Jan 2021
A Survey on Knowledge Graphs: Representation, Acquisition and
  Applications
A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Shaoxiong Ji
Shirui Pan
Erik Cambria
Pekka Marttinen
Philip S. Yu
169
1,877
0
02 Feb 2020
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