Accession Number:

AD1031379

Title:

A PLUG-AND-PLAY ARCHITECTURE FOR PROBABILISTIC PROGRAMMING

Descriptive Note:

Technical Report,01 Jun 2014,30 Jun 2016

Corporate Author:

LogicBlox, Inc Atlanta United States

Personal Author(s):

• Aref,Molham
• Kassios,Yannis
• Kimelfeld,Benny
• Pasalic,Emir
• Vagena,Zografoula

Report Date:

2017-04-01

Pagination or Media Count:

42.0

Abstract:

In the probabilistic-programming paradigm, the application logic is specified by means of a description of a probabilistic model by stating how a sample is being produced using a Probabilistic Programming Language PPL. The principal value one obtains from a probabilistic program lies in the inference thereof, that is, reasoning about the entire probability distribution that the program defines e.g., finding a likely event or estimating its marginal probability. The PPAML kickoff meeting highlighted several research challenges regarding the development of inference infrastructure for PPL, for both increasing software efficiency and reducing software complexity, towards the goal of broadening the PPL applications and the community of implementers and programmers. These challenges include the design of an Application Program Interface API, or alternatively an Intermediate Representation Language IRL, that would allow new solvers to be plugged into existing PPLs, and for PPL engines to be able to pick from and combine solvers for a given problem.

Descriptors:

• MACHINE LEARNING
• probabilistic models
• probability distributions
• random variables
• computer programs
• monte carlo method
• application software
• algorithms
• programming languages
• database management systems
• digital data
• artificial intelligence
• computer programming

Subject Categories:

• Computer Programming and Software

Distribution Statement:

APPROVED FOR PUBLIC RELEASE