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Statistical theory / Gaussian function / Normal distribution / Moment / Maximum likelihood / Central limit theorem / Logarithm / Expected value / Error function / Mathematical analysis / Statistics / Mathematics


Moment-based Uniform Deviation Bounds for k-means and Friends Matus Telgarsky Sanjoy Dasgupta Computer Science and Engineering, UC San Diego {mtelgars,dasgupta}@cs.ucsd.edu
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Document Date: 2013-11-09 00:58:53

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Oxford University Press / P 2 Hf / Springer Publishing Company Incorporated / /

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China / /

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Facility

The Hebrew University of Jerusalem / /

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constant time approximation algorithms / moment tools / Online Learning / basic tool / /

Organization

National Science Foundation / Hebrew University of Jerusalem / Oxford University / /

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Gbor Lugosi / David Pollard / Ulrike Von Luxburg / Stavros A. Zenios / Kenneth Zeger / Richard O. Duda / Alexander Rakhlin / Aad van der Vaart / Peter E. Hart / Thomas S. Ferguson / Bernard Seckler / Inderjit S. Dhillon / Al Censor / Jon A. Wellner / Pascal Massart / Jon Wellner / Claude Lemar´echal / Jean-Baptiste Hiriart-Urruty / Olivier Bousquet / Gao / Joydeep Ghosh / Andrea Caponnetto / Terence Tao / Arindam Banerjee / Srujana Merugu / Sanjoy Dasgupta / /

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Pentax K-x Digital Camera / /

PublishedMedium

Journal of Machine Learning Research / /

Technology

constant time approximation algorithms / specialized tools / p2P / machine learning / /

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