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Paper Abstract and Keywords
Presentation 2024-08-27 13:55
Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer
Ryo Hagiwara, Shunta Arai, Satoshi Takabe (Tokyo Tech) SIP2024-59
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes transfer learning for a trainable sampling-based COP solver applying deep learning technique called deep unfolding (DU), for combinatorial optimization problems (COP). In our previous research, we proposed a deep- -unfolded COP solver that enables learning of the internal parameters of the COP solver that combines a gradient method and a sampler. However, applying DU to QA, which is the original target of the COP solver, is challenging due to a computational cost. We propose classical-quantum transfer learning, which performs the COP solver with the parameters of a solver leared with the classical sampler by QA. Numerical experiments showed that the COP solver with classical-quantum transfer learning significantly accelerated convergence speed compared to the original COP solver.
Keyword (in Japanese) (See Japanese page) 
(in English) Combinatorial Optimization Problems / Sampling / Quantum Annealing / Deep Learning / Deep Unfolding / Transfer Learning / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 162, SIP2024-59, pp. 69-74, Aug. 2024.
Paper # SIP2024-59 
Date of Issue 2024-08-19 (SIP) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SIP2024-59

Conference Information
Committee SIP  
Conference Date 2024-08-26 - 2024-08-27 
Place (in Japanese) (See Japanese page) 
Place (in English) University of Fukui (Bunkyo Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Signal processing, etc. 
Paper Information
Registration To SIP 
Conference Code 2024-08-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer 
Sub Title (in English)  
Keyword(1) Combinatorial Optimization Problems  
Keyword(2) Sampling  
Keyword(3) Quantum Annealing  
Keyword(4) Deep Learning  
Keyword(5) Deep Unfolding  
Keyword(6) Transfer Learning  
Keyword(7)  
Keyword(8)  
1st Author's Name Ryo Hagiwara  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
2nd Author's Name Shunta Arai  
2nd Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
3rd Author's Name Satoshi Takabe  
3rd Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
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Speaker Author-1 
Date Time 2024-08-27 13:55:00 
Presentation Time 20 minutes 
Registration for SIP 
Paper # SIP2024-59 
Volume (vol) vol.124 
Number (no) no.162 
Page pp.69-74 
#Pages 6 
Date of Issue 2024-08-19 (SIP) 

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