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pro vyhledávání: '"Bo, Jianyuan"'
Autor:
Bo, Jianyuan, Fang, Yuan
Graph matching has important applications in pattern recognition and beyond. Current approaches predominantly adopt supervised learning, demanding extensive labeled data which can be limited or costly. Meanwhile, self-supervised learning methods for
Externí odkaz:
http://arxiv.org/abs/2406.17199
Autor:
Yu, Xingtong, Fang, Yuan, Liu, Zemin, Wu, Yuxia, Wen, Zhihao, Bo, Jianyuan, Zhang, Xinming, Hoi, Steven C. H.
Graph representation learning, a critical step in graph-centric tasks, has seen significant advancements. Earlier techniques often operate in an end-to-end setting, which heavily rely on the availability of ample labeled data. This constraint has spu
Externí odkaz:
http://arxiv.org/abs/2402.01440
In this paper, we propose a hybrid framework to solve large-scale permutation-based combinatorial problems effectively using a high-performance quadratic unconstrained binary optimization (QUBO) solver. To do so, transformations are required to chang
Externí odkaz:
http://arxiv.org/abs/2009.12767