Efficient Ising Model Mapping for Induced Subgraph Isomorphism Problems Using Ising Machines

Author(s):  
Natsuhito Yoshimura ◽  
Masashi Tawada ◽  
Shu Tanaka ◽  
Junya Arai ◽  
Satoshi Yagi ◽  
...  
2017 ◽  
Vol 697 ◽  
pp. 69-78 ◽  
Author(s):  
Faisal N. Abu-Khzam ◽  
Édouard Bonnet ◽  
Florian Sikora

2015 ◽  
Vol 562 ◽  
pp. 252-269 ◽  
Author(s):  
Pinar Heggernes ◽  
Pim van 't Hof ◽  
Daniel Meister ◽  
Yngve Villanger

2020 ◽  
Vol 34 (03) ◽  
pp. 2392-2399
Author(s):  
Yanli Liu ◽  
Chu-Min Li ◽  
Hua Jiang ◽  
Kun He

The performance of a branch-and-bound (BnB) algorithm for maximum common subgraph (MCS) problem and its related problems, like maximum common connected subgraph (MCCS) and induced Subgraph Isomorphism (SI), crucially depends on the branching heuristic. We propose a branching heuristic inspired from reinforcement learning with a goal of reaching a tree leaf as early as possible to greatly reduce the search tree size. Experimental results show that the proposed heuristic consistently and significantly improves the current best BnB algorithm for the MCS, MCCS and SI problems. An analysis is carried out to give insight on why and how reinforcement learning is useful in the new branching heuristic.


2021 ◽  
Vol E104.D (4) ◽  
pp. 481-489
Author(s):  
Natsuhito YOSHIMURA ◽  
Masashi TAWADA ◽  
Shu TANAKA ◽  
Junya ARAI ◽  
Satoshi YAGI ◽  
...  

2021 ◽  
Vol 212 (4) ◽  
Author(s):  
Maksim Evgen'evich Zhukovskii ◽  
Eremei Denisovich Kudryavtsev ◽  
Mikhail Vladimirovich Makarov ◽  
Aleksandra Sergeevna Shlychkova

Author(s):  
Sho Kanamaru ◽  
Daisuke Oku ◽  
Masashi Tawada ◽  
Shu Tanaka ◽  
Masato Hayashi ◽  
...  

2015 ◽  
Vol 605 ◽  
pp. 119-128 ◽  
Author(s):  
Peter Floderus ◽  
Mirosław Kowaluk ◽  
Andrzej Lingas ◽  
Eva-Marta Lundell

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