Probabilistic Programming for Advancing Machine Learning
Machine Learning is at the heart of modern approaches to artificial intelligence. The field posits that teaching computers how to learn can be significantly more effective than programming them explicitly. Unfortunately, building effective machine learning applications currently still requires Herculean efforts on the part of highly trained experts in machine learning.
Probabilistic Programming is a new programming paradigm for managing uncertain information. The goal of the Probabilistic Programming for Advancing Machine Learning (PPAML) program is to facilitate the construction of machine learning applications by using probabilistic programming to:
The PPAML program started in November 2013 and is scheduled to run 46 months, with three phases of activity through 2017.
Modified Fri Mar 10 17:03:17 2017 by Eric.Woldridge.