Professor Richard Samworth | Department of Pure Mathematics and Mathematical Statistics

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Professor of Statistics and Director of Statistical Laboratory

Research Interests: Nonparametric and high-dimensional statistics

Publications

High-probability minimax lower bounds

T Ma, KA Verchand, RJ Samworth

(2024)

(link to publication)

A new computational framework for log-concave density estimation

W Chen, R Mazumder, RJ Samworth

– Mathematical Programming Computation

(2024)

16,

185

(doi: 10.1007/s12532-024-00252-0)

Optimal convex $M$-estimation via score matching

OY Feng, Y-C Kao, M Xu, RJ Samworth

(2024)

(link to publication)

Optimal subgroup selection

HWJ Reeve, TI Cannings, RJ Samworth

– Annals of Statistics

(2023)

51,

2342

(doi: 10.1214/23-aos2328)

Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility

TB Berrett, RJ Samworth

– Annals of Statistics

(2023)

51,

2170

(doi: 10.1214/23-AOS2326)

Inference in High-Dimensional Online Changepoint Detection

Y Chen, T Wang, RJ Samworth

– J Am Stat Assoc

(2023)

ahead-of-print,

1461

(doi: 10.1080/01621459.2023.2199962)

Isotonic subgroup selection

MM Müller, HWJ Reeve, TI Cannings, RJ Samworth

(2023)

(link to publication)

Sharp-SSL: Selective high-dimensional axis-aligned random projections for semi-supervised learning

T Wang, E Dobriban, M Gataric, RJ Samworth

(2023)

(link to publication)

Efficient functional estimation and the super-oracle phenomenon

TB Berrett, RJ Samworth

– The Annals of Statistics

(2023)

51,

668

(doi: 10.1214/23-aos2265)

High-Dimensional Principal Component Analysis with Heterogeneous Missingness

Z Zhu, T Wang, RJ Samworth

– Journal of the Royal Statistical Society. Series B: Statistical Methodology

(2022)

84,

2000

(doi: 10.1111/rssb.12550)