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Adaptation in multivariate log-concave density estimation Kim, Arlene Kyoung Hee
Description
The log-concave maximum likelihood estimator of a density on $\mathbb R^d$ on a sample of size n is known to attain the minimax optimal rate of convergence up to a log factor when $d=2$ and $d=3$. In this talk, I will present new results on adaptation properties in this multivariate setting. This is based on joint work with Oliver Feng, Aditya Guntuboyina and Richard Samworth.
Item Metadata
| Title |
Adaptation in multivariate log-concave density estimation
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| Creator | |
| Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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| Date Issued |
2018-01-29T14:05
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| Description |
The log-concave maximum likelihood estimator of a density on $\mathbb R^d$ on a sample of size n is known to attain the minimax optimal rate of convergence up to a log factor when $d=2$ and $d=3$. In this talk, I will present new results on adaptation properties in this multivariate setting. This is based on joint work with Oliver Feng, Aditya Guntuboyina and Richard Samworth.
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| Extent |
41.0 minutes
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| Subject | |
| Type | |
| File Format |
video/mp4
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| Language |
eng
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| Notes |
Author affiliation: University of Cambridge and Sungshin Women's university
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| Series | |
| Date Available |
2020-12-07
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0395167
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| URI | |
| Affiliation | |
| Peer Review Status |
Unreviewed
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| Scholarly Level |
Faculty
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International