Permanents and modeling probability distributions

August 31 to September 4, 2009

at the

American Institute of Mathematics, Palo Alto, California

organized by

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.

Material from the workshop

A list of participants.

The workshop schedule.

A report on the workshop activities.