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» Simplifying Probabilistic Programs Using Computer Algebra
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GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
15 years 3 months ago
Evolving stochastic processes using feature tests and genetic programming
The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Brian J. Ross, Janine H. Imada
ICDE
2010
IEEE
227views Database» more  ICDE 2010»
15 years 10 months ago
Approximate Confidence Computation in Probabilistic Databases
Abstract-- This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variable...
Dan Olteanu, Jiewen Huang, Christoph Koch
90
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POPL
2009
ACM
15 years 5 months ago
Low-pain, high-gain multicore programming in Haskell: coordinating irregular symbolic computations on multicore architectures
With the emergence of commodity multicore architectures, exploiting tightly-coupled parallelism has become increasingly important. Functional programming languages, such as Haskel...
Abdallah Al Zain, Kevin Hammond, Jost Berthold, Ph...
DISCO
1993
156views Hardware» more  DISCO 1993»
15 years 2 months ago
Variant Handling, Inheritance and Composition in the ObjectMath Computer Algebra Environment
ObjectMath is a high-level programming environment and modeling language for scientific computing which supports variants and graphical browsing in the environment and integrates o...
Peter Fritzson, Vadim Engelson, Lars Viklund
LPAR
2005
Springer
15 years 4 months ago
Towards Automated Proof Support for Probabilistic Distributed Systems
Abstract. The mechanisation of proofs for probabilistic systems is particularly challenging due to the verification of real-valued properties that probability entails: experience ...
Annabelle McIver, Tjark Weber