Alon Orlitsky,
Narayana Santhanam,
and Krishnamurthy Viswanathan

Original Announcement

This workshop will study
the problem of estimating a probability distribution from a small data sample
it generates. The workshop will investigate consolidating a
theoretical and algorithmic framework for this topic.
Aspects addressed will include distribution, probability, and
population estimation, prediction, and classification. Emphasis
will be on recent methods related to Good-Turing estimation
and patterns, which cast the problem in a combinatorial and
machine-learning perspective and relate it to integer and set
partitions, symmetric polynomials over many variables,
computation of matrix permanents, Markov chain Monte Carlo
techniques, universal compression, and geometric
programming.