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UID:GLW_UNI_MS_WEBEVT_11435@maths-stats.gla.ac.uk
DTSTAMP:19700101T000000Z
DTSTART:20250709T130000Z
DTEND:20250709T140000Z
SUMMARY:Statistics Seminar: Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning - Takuo Matsubara (The University of Edinburgh)
DESCRIPTION:Abstract: Gradient boosting is a sequential ensemble method that fits a new weaker learner to pseudo residuals at each iteration. We propose Wasserstein gradient boosting\, a novel extension of gradient boosting that fits a new weak learner to alternative pseudo residuals that are Wasserstein gradients of loss functionals of probability distributions...\N\NMore information: http://www.gla.ac.uk/schools/mathematicsstatistics/events/details/?id=11435
LOCATION:Maths 311B
SEQUENCE:7
STATUS:CONFIRMED
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