Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
A framework for multiple-instance learning
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Multiple-Instance Learning of Real-Valued Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Learning from ambiguity
Improve Multi-Instance Neural Networks through Feature Selection
Neural Processing Letters
Multi-objective Genetic Programming for Multiple Instance Learning
ECML '07 Proceedings of the 18th European conference on Machine Learning
Multiple instance learning with genetic programming for web mining
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Grammar guided genetic programming for multiple instance learning: an experimental study
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Multiple Instance Learning with Multiple Objective Genetic Programming for Web Mining
Applied Soft Computing
G3P-MI: A genetic programming algorithm for multiple instance learning
Information Sciences: an International Journal
HyDR-MI: A hybrid algorithm to reduce dimensionality in multiple instance learning
Information Sciences: an International Journal
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Recently, multi-instance classification algorithm BP-MIP and multiinstance regression algorithm BP-MIR both based on neural networks have been proposed. In this paper, neural network ensemble techniques are introduced to solve multi-instance learning problems, where BP-MIP ensemble and BP-MIR ensemble are constructed respectively. Experiments on benchmark and artificial data sets show that ensembles of multi-instance neural networks are superior to single multi-instance neural networks in solving multiinstance problems.