Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Bounding the Vapnik-Chervonenkis Dimension of Concept Classes Parameterized by Real Numbers
Machine Learning - Special issue on COLT '93
Complexity and real computation
Complexity and real computation
Time-space tradeoffs in algebraic complexity theory
Journal of Complexity
Combinatorial Hardness Proofs for Polynomial Evaluation
MFCS '98 Proceedings of the 23rd International Symposium on Mathematical Foundations of Computer Science
Bounding VC-dimension of neural networks: Progress and prospects
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Lower bounds for algebraic computation trees
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
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We provide upper bounds for the Vapnik-Chervonenkis dimension of classes of subsets of that can be recognized by computer programs built from arithmetical assignments, infinitelydifferentiable algebraic operations(like k-root extraction and, more generally, operations defined by algebraic series of fractional powers), conditional statementsand while instructions. This includes certain classes of GP-trees considered in Genetic Programming for symbolic regression and bi-classification. As a consequence we show explicit quantitative properties that can help to design the fitness function of a GP learning machine.