2010
AISTATS
AISTATS 2010
Gaussian processes with monotonicity information
Abstract
A method for using monotonicity information in multivariate Gaussian process regression and classification is proposed. Monotonicity information is introduced with virtual derivative observations, and the resulting posterior is approximated with expectation propagation. Behaviour of the method is illustrated with artificial regression examples, and the method is used in a real world health care classification problem to include monotonicity information with respect to one of the covariates.
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Conference Pioneer
— AISTATS 2010
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning
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Keyword Pioneer
— monotonicity constraint
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Hot Topic Early Bird
— gaussian process
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
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Trend Setter
— Medical AI