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Probability Estimation over Large Alphabets

Orlitsky, A (UC, San Diego)
Friday 15 January 2010, 09:30-10:30

Seminar Room 1, Newton Institute


Many applications require estimating distributions over large alphabets based on a small data sample. We outline the problem's history, theory, and applications, and describe recent constructions of asymptotically optimal estimators. The talk is self contained and based on work with P. Santhanam, K. Viswanathan, J. Zhang, and others.


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