TY - GEN
T1 - Monolingual probabilistic programming using generalized coroutines
AU - Kiselyov, Oleg
AU - Shan, Chung Chieh
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - Probabilistic programming languages and modeling toolkits are two modular ways to build and reuse stochastic models and inference procedures. Combining strengths of both, we express models and inference as generalized coroutines in the same general-purpose language. We use existing facilities of the language, such as rich libraries, optimizing compilers, and types, to develop concise, declarative, and realistic models with competitive performance on exact and approximate inference. In particular, a wide range of models can be expressed using memoization. Because deterministic parts of models run at full speed, custom inference procedures are trivial to incorporate, and inference procedures can reason about themselves without interpretive overhead. Within this framework, we introduce a new, general algorithm for importance sampling with look-ahead.
AB - Probabilistic programming languages and modeling toolkits are two modular ways to build and reuse stochastic models and inference procedures. Combining strengths of both, we express models and inference as generalized coroutines in the same general-purpose language. We use existing facilities of the language, such as rich libraries, optimizing compilers, and types, to develop concise, declarative, and realistic models with competitive performance on exact and approximate inference. In particular, a wide range of models can be expressed using memoization. Because deterministic parts of models run at full speed, custom inference procedures are trivial to incorporate, and inference procedures can reason about themselves without interpretive overhead. Within this framework, we introduce a new, general algorithm for importance sampling with look-ahead.
UR - http://www.scopus.com/inward/record.url?scp=80053143477&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:80053143477
T3 - Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009
SP - 285
EP - 292
BT - Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009
PB - AUAI Press
ER -