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Preface: case-based reasoning and deep learning.

Martin, Kyle; Kapetanakis, Stelios; Wijekoon, Ajana; Amin, Kareem; Massie, Stewart

Authors

Stelios Kapetanakis

Ajana Wijekoon

Kareem Amin



Contributors

Stelios Kapetanakis
Editor

Hayley Borck
Editor

Abstract

Recent advances in deep learning (DL) have helped to usher in a new wave of confidence in the capability of artificial intelligence. Increasingly, we are seeing DL architectures out perform long established state-of-the-art algorithms in a number of diverse tasks. In fact, DL has reached a point where it currently rivals or has surpassed human performance in a number of challenges e.g. image classification, speech recognition and game play.

Citation

MARTIN, K., KAPETANAKIS, S., WIJEKOON, A., AMIN, K. and MASSIE, S. 2019. Preface: case-based reasoning and deep learning. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 27th International conference on case-based reasoning workshop (ICCBR-WS19), co-located with the 27th International conference on case-based reasoning (ICCBR19), 8-12 September 2019, Otzenhausen, Germany. CEUR workshop proceedings, 2567. Aachen: CEUR-WS [online], pages 6-7. Available from: http://ceur-ws.org/Vol-2567/cbr_dl_preface.pdf

Presentation Conference Type Conference Paper (published)
Conference Name 27th International conference on case-based reasoning workshop (ICCBR-WS19), co-located with the 27th International conference on case-based reasoning (ICCBR19)
Start Date Sep 8, 2019
End Date Sep 12, 2019
Acceptance Date Jul 23, 2019
Online Publication Date Mar 4, 2020
Publication Date Mar 4, 2020
Deposit Date Apr 7, 2020
Publicly Available Date Apr 7, 2020
Publisher CEUR-WS
Peer Reviewed Peer Reviewed
Pages 6-7
Series Title CEUR workshop proceedings
Series Number 2567
Series ISSN 1613-0073
Keywords Learning theory; Representation learning; Deep learning architectures; Hybrid systems; Deep reinforcement learning; Deep belief networks; Auto-encoders; Feed-forward neural networks; Convolutional neural networks; Recurrent neural networks; Generative adv
Public URL https://rgu-repository.worktribe.com/output/891532
Publisher URL http://ceur-ws.org/Vol-2567/cbr_dl_preface.pdf

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