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- 01GP0X34Y51ZAF3RNMH631K7Z6 classification A1.
- 01GP0X34Y51ZAF3RNMH631K7Z6 date "2023".
- 01GP0X34Y51ZAF3RNMH631K7Z6 language "eng".
- 01GP0X34Y51ZAF3RNMH631K7Z6 type journalArticle.
- 01GP0X34Y51ZAF3RNMH631K7Z6 hasPart 01GP0X5GGFNKE66MAFQKD6HT6C.pdf.
- 01GP0X34Y51ZAF3RNMH631K7Z6 subject "Technology and Engineering".
- 01GP0X34Y51ZAF3RNMH631K7Z6 doi "10.1515/nanoph-2022-0399".
- 01GP0X34Y51ZAF3RNMH631K7Z6 issn "2192-8606".
- 01GP0X34Y51ZAF3RNMH631K7Z6 issn "2192-8614".
- 01GP0X34Y51ZAF3RNMH631K7Z6 issue "5".
- 01GP0X34Y51ZAF3RNMH631K7Z6 volume "12".
- 01GP0X34Y51ZAF3RNMH631K7Z6 abstract "Photonic reservoir computing has been demonstrated to be able to solve various complex problems. Although training a reservoir computing system is much simpler compared to other neural network approaches, it still requires considerable amounts of resources which becomes an issue when retraining is required. Transfer learning is a technique that allows us to re-use information between tasks, thereby reducing the cost of retraining. We propose transfer learning as a viable technique to compensate for the unavoidable parameter drift in experimental setups. Solving this parameter drift usually requires retraining the system, which is very time and energy consuming. Based on numerical studies on a delay-based reservoir computing system with semiconductor lasers, we investigate the use of transfer learning to mitigate these parameter fluctuations. Additionally, we demonstrate that transfer learning applied to two slightly different tasks allows us to reduce the amount of input samples required for training of the second task, thus reducing the amount of retraining.".
- 01GP0X34Y51ZAF3RNMH631K7Z6 author F55201D6-F0ED-11E1-A9DE-61C894A0A6B4.
- 01GP0X34Y51ZAF3RNMH631K7Z6 author urn:uuid:07e6ac0c-7d8e-4bcb-a59d-c6264416d8ed.
- 01GP0X34Y51ZAF3RNMH631K7Z6 author urn:uuid:778284c2-8a67-4abe-8275-1682a492d470.
- 01GP0X34Y51ZAF3RNMH631K7Z6 author urn:uuid:f119a7ce-0c5e-4896-a627-2747372325b7.
- 01GP0X34Y51ZAF3RNMH631K7Z6 author urn:uuid:fa8f0ddf-82c2-4611-8838-6c69748f34af.
- 01GP0X34Y51ZAF3RNMH631K7Z6 dateCreated "2023-01-05T12:04:33Z".
- 01GP0X34Y51ZAF3RNMH631K7Z6 dateModified "2024-12-12T17:59:08Z".
- 01GP0X34Y51ZAF3RNMH631K7Z6 name "Transfer learning for photonic delay-based reservoir computing to compensate parameter drift".
- 01GP0X34Y51ZAF3RNMH631K7Z6 pagination urn:uuid:678d97bc-dd53-4254-b731-d45c9c5c7a95.
- 01GP0X34Y51ZAF3RNMH631K7Z6 sameAs LU-01GP0X34Y51ZAF3RNMH631K7Z6.
- 01GP0X34Y51ZAF3RNMH631K7Z6 sourceOrganization urn:uuid:480c672e-d980-4b09-b030-1a862602fe5e.
- 01GP0X34Y51ZAF3RNMH631K7Z6 sourceOrganization urn:uuid:e259ada2-a2f7-4b6b-843a-723701e3aebf.
- 01GP0X34Y51ZAF3RNMH631K7Z6 type A1.