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Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Learning.
Jiajin Li
Jianheng Tang
Lemin Kong
Huikang Liu
Jia Li
Anthony Man-Cho So
Jose H. Blanchet
Published in:
CoRR (2022)
Keyphrases
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provably convergent
learning algorithm
learning process
shape from shading
learning problems
learning tasks
noise tolerant
learning models
learning systems
significant improvement
computational complexity
graph theory
active learning
video sequences
graph model
depth first search
image processing
feature selection