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  • title: Christoffel Sampling for Machine Learning (CS4ML): A general framework for active learning with arbitrary data based on Christoffel functions
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            Christoffel Sampling for Machine Learning (CS4ML): A general framework for active learning with arbitrary data based on Christoffel functions
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            Christoffel Sampling for Machine Learning (CS4ML): A general framework for active learning with arbitrary data based on Christoffel functions

            Dec 10, 2023

            Speakers

            BA

            Ben Adcock

            Řečník · 0 sledujících

            JMC

            Juan M. Cardenas

            Řečník · 0 sledujících

            ND

            Nick Dexter

            Řečník · 0 sledujících

            About

            We introduce a general framework for active learning in regression problems. Our framework extends the standard setup by allowing for general types of data, rather than merely pointwise samples of the target function. This generalization covers many cases of practical interest, such as data acquired in transform domains (e.g., Fourier data), vector-valued data (e.g., gradient-augmented data), data acquired along continuous curves, and, multimodal data (i.e., combinations of different types of me…

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            NeurIPS 2023

            Účet · 615 sledujících

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