Popularity Prediction for Social Media over Arbitrary Time Horizons
Daniel Haimovich, Dima Karamshuk, Thomas J. Leeper, Evgeniy Riabenko, Milan Vojnovic
HackPPL: A Universal Probabilistic Programming Language
MAPL at PLDI
Abstract
HackPPL is a probabilistic programming language (PPL) built within the Hack programming language. Its universal inference engine allows developers to perform inference across a diverse set of models expressible in arbitrary Hack code. Through language-level extensions and direct integration with developer tools, HackPPL aims to bridge the gap between domain-specific and embedded PPLs. This paper overviews the design and implementation choices for the HackPPL toolchain and presents findings by applying it to a representative problem faced by social media companies.
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