Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Genetic programming II (videotape): the next generation
Genetic programming II (videotape): the next generation
Using Generative Models for Handwritten Digit Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning - Special issue on inductive transfer
PADO: a new learning architecture for object recognition
Symbolic visual learning
ICES '96 Proceedings of the First International Conference on Evolvable Systems: From Biology to Hardware
Evolving Modules in Genetic Programming by Subtree Encapsulation
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Collective adaptation: the sharing of building blocks
Collective adaptation: the sharing of building blocks
Generative Models and Bayesian Model Comparison for Shape Recognition
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Learning Multiple Tasks with Kernel Methods
The Journal of Machine Learning Research
Learning Gaussian processes from multiple tasks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Knowledge reuse in genetic programming applied to visual learning
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Generative learning of visual concepts using multiobjective genetic programming
Pattern Recognition Letters
Learning and Recognition of Hand-Drawn Shapes Using Generative Genetic Programming
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
The honeybee search algorithm for three-dimensional reconstruction
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Learning high-level visual concepts using attributed primitives and genetic programming
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Evolving pattern recognition systems
IEEE Transactions on Evolutionary Computation
Visual learning by coevolutionary feature synthesis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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We propose a multitask learning method of visual concepts within the genetic programming (GP) framework. Each GP individual is composed of several trees that process visual primitives derived from input images. Two trees solve two different visual tasks and are allowed to share knowledge with each other by commonly calling the remaining GP trees (subfunctions) included in the same individual. The performance of a particular tree is measured by its ability to reproduce the shapes contained in the training images. We apply this method to visual learning tasks of recognizing simple shapes and compare it to a reference method. The experimental verification demonstrates that such multitask learning often leads to performance improvements in one or both solved tasks, without extra computational effort.