- author = "Keith M. Sullivan and Sean Luke",
- title = "Evolving kernels for support vector machine classification",
- booktitle = "GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation",
- year = "2007",
- editor = "Dirk Thierens and Hans-Georg Beyer and Josh Bongard and Jurgen Branke and John Andrew Clark and Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and Julian F. Miller and Jason Moore and Frank Neumann and Martin Pelikan and Riccardo Poli and Kumara Sastry and Kenneth Owen Stanley and Thomas Stutzle and Richard A Watson and Ingo Wegener",
- volume = "2",
- isbn13 = "978-1-59593-697-4",
- pages = "1702--1707",
- address = "London",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gecco2007/docs/p1702.pdf",
-
DOI = "
doi:10.1145/1276958.1277292",
- publisher = "ACM Press",
- publisher_address = "New York, NY, USA",
- month = "7-11 " # jul,
- organisation = "ACM SIGEVO (formerly ISGEC)",
- keywords = "genetic algorithms, genetic programming, Support Vector Machines, SVM, STGP, ECJ",
- size = "6 pages",
- abstract = "While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM's kernel function. This project seeks to replace this expert with a genetic programming (GP) system. Using strongly typed genetic programming and principled kernel closure properties, we introduce a new algorithm, called KGP, which finds near-optimal kernels. The algorithm shows wide applicability, but the combined computational overhead of GP and SVMs remains a major unresolved issue.",
-
notes = "GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).
ACM Order Number 910071
Cites \cite{DBLP:journals/air/HowleyM05}. Guarantees closure and evolved kernel is valid (ie it will be a Mercer Kernel). Positive definite gram matrix => Mercer Kernel
C-SVC, u-SVC
LIBSVM Mentions total noise datasets (ie Pima, page 1705) but does not give results. KGP. Not obvious why evolved kernels work. Small difference between GP SVM (KGP) and SVM-Grid?",
