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# Kenneth L. Clarkson

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USA-2008

For contributions to computational geometry.

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My work has mainly been on geometric algorithms, and in particular on algorithms that have provable properties, but are relatively simple. Randomization is quite useful for this, whether via the Vapnik-Chervonenkis dimension, or using the general framework I introduced here. See, for example, a (somewhat dated) survey on randomized geometric algorithms.

## Papers98 papers

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international conference on machine learning, (2019): 1262-1271

MICCAI, pp.543-551, (2018)

SODA, pp.2061-2072, (2017)

SODA '17: Symposium on Discrete Algorithms
Barcelona
Spain
January, 2017, pp.2061-2072, (2017)

Journal of the ACM (JACM), no. 6 (2017)

SIAM J. Matrix Analysis Applications, no. 4 (2017)

international workshop and international workshop on approximation randomization and combinatorial o..., (2017): 27:1-27:22

arXiv: Data Structures and Algorithms, (2016)

Discrete & Computational Geometry, no. 4 (2016): 745-747

SIAM J. Comput., no. 3 (2016): 763-810

IEEE Symposium on Foundations of Computer Science, (2015)

(2014)

Cited by

**1**BibtexSIAM Journal on Computing, no. 2 (2014): 617-653

Proceedings of the forty-fifth annual ACM symposium on Theory of computing, (2013)

SODA '13: ACM-SIAM Symposium on Discrete Algorithms
New Orleans
Louisiana
Janu..., pp.466-477, (2013)

Yoshiyuki Nishizeki,Alfred V Aho, John E Hopcroft,Jeffrey D Ullman,Kenneth L Clarkson,Shiv G Kapoor,Pravin M Vaidya, Elmer G Gilbert, D W Johnson, Distance Functions

(2013)

Bibtex

Kenneth L. Clarkson,Petros Drineas, Malik Magdon-Ismail,Michael W. Mahoney,Xiangrui Meng,David P. Woodruff

CoRR, (2012)

Proceedings of the twenty-eighth annual symposium on Computational geometry, (2012)

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