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Cantab Capital Institute for the Mathematics of Information

University Lecturer

Research Interests: High-dimensional statistics and large-scale data analysis

Publications

The xyz algorithm for fast interaction search in high-dimensional data
GA Thanei, N Meinshausen, RD Shah
– Journal of Machine Learning Research
(2018)
19,
ARTN 37
On b-bit Min-wise Hashing for Large-scale Regression and Classification with Sparse Data
RD Shah, N Meinshausen
– Journal of Machine Learning Research
(2018)
18,
1
Goodness‐of‐fit tests for high dimensional linear models
RD Shah, P Bühlmann
– Journal of the Royal Statistical Society. Series B: Statistical Methodology
(2017)
80,
113
Modelling Interactions in High-dimensional Data with Backtracking
RD Shah
– Journal of Machine Learning Research
(2016)
17,
1
Modelling interactions in high-dimensional data with backtracking
RD Shah
– Journal of Machine Learning Research
(2016)
17,
1
Comment
RD Shah, RJ Samworth
– Journal of the American Statistical Association
(2016)
110,
1439
An Adaptive Resampling Test for Detecting the Presence of Significant Predictors Comment
RD Shah, RJ Samworth
– JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2015)
110,
1439
Diffuse large B-cell lymphoma classification system that associates normal B-cell subset phenotypes with prognosis
K Dybkær, M Bøgsted, S Falgreen, JS Bødker, MK Kjeldsen, A Schmitz, AE Bilgrau, ZY Xu-Monette, L Li, KS Bergkvist, MB Laursen, M Rodrigo-Domingo, SC Marques, SB Rasmussen, M Nyegaard, M Gaihede, MB Møller, RJ Samworth, RD Shah, P Johansen, TC El-Galaly, KH Young, HE Johnsen
– Journal of Clinical Oncology
(2015)
33,
1379
Random intersection trees
RD Shah, N Meinshausen
– Journal of Machine Learning Research
(2014)
15,
629
Discussion of 'Correlated variables in regression: Clustering and sparse estimation' by Peter Buhlmann, Philipp Rutimann, Sara van de Geer and Cun-Hui Zhang
RD Shah, RJ Samworth
– Journal of Statistical Planning and Inference
(2013)
143,
1866
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Research Group

Cantab Capital Institute for the Mathematics of Information

Room

D1.15

Telephone

01223 765923