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» On Learning Limiting Programs
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AUSAI
2001
Springer
15 years 5 months ago
An Investigation of an Adaptive Poker Player
: Other work has shown that adaptive learning can be highly successful in developing programs which are able to play games at a level similar to human players and, in some cases, e...
Graham Kendall, Mark Willdig
121
Voted
JMLR
2010
155views more  JMLR 2010»
14 years 11 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
130
Voted
ICML
2007
IEEE
16 years 1 months ago
Discriminant kernel and regularization parameter learning via semidefinite programming
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
Jieping Ye, Jianhui Chen, Shuiwang Ji
107
Voted
ICML
1998
IEEE
16 years 1 months ago
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
Ricardo Aler, Daniel Borrajo, Pedro Isasi
107
Voted
ICFP
2006
ACM
16 years 14 days ago
Good advice for type-directed programming aspect-oriented programming and extensible generic functions
Type-directed programming is an important idiom for software design. In type-directed programming the behavior of programs is guided by the type structure of data. It makes it pos...
Geoffrey Washburn, Stephanie Weirich