Accelerating GPU-based Evolutionary Induction of Decision Trees - Fitness Evaluation Reuse-Reference-Cited by-同舟云学术

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Accelerating GPU-based Evolutionary Induction of Decision Trees - Fitness Evaluation Reuse

Published:2020 Issue: Volume: Page:421-431
ISSN:0302-9743
Container-title:Parallel Processing and Applied Mathematics
language:
Short-container-title:

Author:

Jurczuk Krzysztof^ORCID,Czajkowski Marcin^ORCID,Kretowski Marek^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-43229-4_36

Reference18 articles.

1. NVIDIA Developer Zone - CUDA Toolkit Documentation (2019). https://docs.nvidia.com/cuda/cuda-c-programming-guide/

2. Barros, R.C., Basgalupp, M.P., De Carvalho, A.C., Freitas, A.A.: A survey of evolutionary algorithms for decision-tree induction. IEEE Trans. SMC, Part C 42(3), 291–312 (2012)

3. Charalampakis, A.E.: Registrar: a complete-memory operator to enhance performance of genetic algorithms. J. Glob. Optim. 54(3), 449–483 (2012)

4. Chitty, D.M.: Fast parallel genetic programming: multi-core CPU versus many-core GPU. Soft Comput. 16(10), 1795–1814 (2012)

5. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);M Czajkowski,2015

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Parallel Extremely Randomized Decision Forests on Graphics Processors for Text Classification;Parallel Processing and Applied Mathematics;2023

2. Fitness evaluation reuse for accelerating GPU-based evolutionary induction of decision trees;The International Journal of High Performance Computing Applications;2020-09-15

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