Richard Samworth

Results: 23



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1High-dimensional nonparametric density estimation via symmetry and shape constraints Min Xu∗and Richard J. Samworth† Wharton Business School, University of Pennsylvania and Statistical Laboratory, University of Cambr

High-dimensional nonparametric density estimation via symmetry and shape constraints Min Xu∗and Richard J. Samworth† Wharton Business School, University of Pennsylvania and Statistical Laboratory, University of Cambr

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Source URL: www.statslab.cam.ac.uk

Language: English - Date: 2017-09-11 03:39:43
    2J. R. Statist. Soc. BHigh dimensional change point estimation via sparse projection Tengyao Wang and Richard J. Samworth University of Cambridge, UK

    J. R. Statist. Soc. BHigh dimensional change point estimation via sparse projection Tengyao Wang and Richard J. Samworth University of Cambridge, UK

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    Source URL: www.statslab.cam.ac.uk

    Language: English - Date: 2017-08-12 12:44:15
      3Optimal weighted nearest neighbour classifiers Richard Samworth University of Cambridge

      Optimal weighted nearest neighbour classifiers Richard Samworth University of Cambridge

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      Source URL: www.statslab.cam.ac.uk

      Language: English - Date: 2012-09-21 14:04:38
        4Discussion of Stability Selection by Meinshausen and Buhlmann ¨ Rajen Shah and Richard Samworth University of Cambridge

        Discussion of Stability Selection by Meinshausen and Buhlmann ¨ Rajen Shah and Richard Samworth University of Cambridge

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        Source URL: www.statslab.cam.ac.uk

        Language: English - Date: 2010-05-03 05:56:31
          5H IGH - DIMENSIONAL VARIABLE SELECTION IN S TATISTICS Richard Samworth University of Cambridge Joint work with Rajen Shah

          H IGH - DIMENSIONAL VARIABLE SELECTION IN S TATISTICS Richard Samworth University of Cambridge Joint work with Rajen Shah

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          Source URL: www.statslab.cam.ac.uk

          Language: English - Date: 2012-09-21 07:41:56
            6Estimation of adult skeletal age-at-death: statistical assumptions and applications Richard Samworth and Rebecca Gowland Statistical Laboratory Centre for Mathematical Sciences

            Estimation of adult skeletal age-at-death: statistical assumptions and applications Richard Samworth and Rebecca Gowland Statistical Laboratory Centre for Mathematical Sciences

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            Source URL: www.statslab.cam.ac.uk

            Language: English - Date: 2006-02-03 11:57:04
              7Rejoinder to Maximum likelihood estimation of a multidimensional log-concave density Madeleine Cule and Richard Samworth† University of Cambridge, UK and Michael Stewart University of Sydney, Australia

              Rejoinder to Maximum likelihood estimation of a multidimensional log-concave density Madeleine Cule and Richard Samworth† University of Cambridge, UK and Michael Stewart University of Sydney, Australia

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              Source URL: www.statslab.cam.ac.uk

              Language: English - Date: 2010-08-24 10:44:32
                8Importance Tempering Robert Gramacy & Richard Samworth Statistical Laboratory University of Cambridge {bobby, rjs57}@statslab.cam.ac.uk

                Importance Tempering Robert Gramacy & Richard Samworth Statistical Laboratory University of Cambridge {bobby, rjs57}@statslab.cam.ac.uk

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                Source URL: www.statslab.cam.ac.uk

                Language: English - Date: 2008-11-03 13:20:58
                  9Discussion of Adaptive confidence intervals for the test error in classification by Laber and Murphy Richard J. Samworth Statistical Laboratory University of Cambridge

                  Discussion of Adaptive confidence intervals for the test error in classification by Laber and Murphy Richard J. Samworth Statistical Laboratory University of Cambridge

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                  Source URL: www.statslab.cam.ac.uk

                  Language: English - Date: 2011-03-11 13:40:34
                    10Discussion of Sure independence screening for ultrahigh dimensional feature space by Fan and Lv Richard Samworth† University of Cambridge, UK I would like to congratulate the authors for a very interesting and timely c

                    Discussion of Sure independence screening for ultrahigh dimensional feature space by Fan and Lv Richard Samworth† University of Cambridge, UK I would like to congratulate the authors for a very interesting and timely c

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                    Source URL: www.statslab.cam.ac.uk

                    Language: English - Date: 2008-04-24 15:12:05