Approximation of Ridge Functions and Sparse Additive Models
39 mins 51 secs,
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About this item
| Description: |
Vybiral, J
Monday 18th February 2019 - 13:40 to 14:15 |
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| Created: | 2019-02-19 13:26 |
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| Collection: | Approximation, sampling and compression in data science |
| Publisher: | Isaac Newton Institute |
| Copyright: | Vybiral, J |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | The approximation of smooth multivariate functions is known to suffer the curse of dimension. We discuss approximation of structured multivariate functions, which take the form of a ridge, their sum, or of the so-called sparse additive models. We give also results about optimality of such algorithms.
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