Genetic Programming Bibliography entries for Thomas Loveard
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GP coauthors/coeditors:
Victor Ciesielski,
Andy Song,
Genetic Programming PhD doctoral thesis Thomas Loveard
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Thomas Loveard.
Genetic Programming for Classification Learning Problems. PhD thesis,
Department of Computer Science, Royal Melbourne Institute of Technology, RMIT, Australia, 2003.
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Genetic Programming conference papers by Thomas Loveard
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Thomas Loveard.
Genetic Programming With Meta-Search: Searching For a Successful Population Within The Classification Domain. In
Conor Ryan and Terence Soule and Maarten Keijzer and Edward Tsang and Riccardo Poli and Ernesto Costa editors,
Genetic Programming, Proceedings of EuroGP'2003, volume 2610, pages 119-129, Essex, 2003. Springer-Verlag.
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Thomas Loveard and Vic Ciesielski.
Employing Nominal Attributes in Classification Using Genetic Programming. In
Lipo Wang and Kay Chen Tan and Takeshi Furuhashi and Jong-Hwan Kim and Xin Yao editors,
Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL'02), pages 487-491, Orchid Country Club, Singapore, 2002. IEEE.
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Thomas Loveard and Vic Ciesielski.
Genetic Programming for Classification: An Analysis of Convergence Behaviour. In
Bob McKay and John Slaney editors,
AI 2002: Advances in Artificial Intelligence : 15th Australian Joint Conference on Artificial Intelligence, volume 2557, pages 309-320, Canberra, Australia, 2002. Springer.
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Andy Song and Thomas Loveard and Vic Ciesielski.
Towards Genetic Programming for Texture Classification. In
M. Stumptner and D. Corbett and M. Brooks editors,
Proceedings of the 14th International Joint Conference on Artificial Intelligence AI 2001: Advances in Artificial Intelligence, volume 2256, pages 461-472, Adelaide, Australia, 2001. Springer-Verlag.
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Thomas Loveard and Victor Ciesielski.
Representing Classification Problems in Genetic Programming. In
Proceedings of the Congress on Evolutionary Computation, volume 2, pages 1070-1077, COEX, World Trade Center, 159 Samseong-dong, Gangnam-gu, Seoul, Korea, 2001. IEEE Press.
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