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FUIN
2008
108views more  FUIN 2008»
14 years 9 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
ICFP
2007
ACM
15 years 11 months ago
Stream fusion: from lists to streams to nothing at all
This paper presents an automatic deforestation system, stream fusion, based on equational transformations, that fuses a wider range of functions than existing short-cut fusion sys...
Duncan Coutts, Roman Leshchinskiy, Don Stewart
ENTCS
2006
142views more  ENTCS 2006»
14 years 11 months ago
The Rewriting Logic Semantics Project
Rewriting logic is a flexible and expressive logical framework that unifies algebraic denotational semantics and structural operational semantics (SOS) in a novel way, avoiding th...
José Meseguer, Grigore Rosu
ESOP
2011
Springer
14 years 2 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
AGENTS
2001
Springer
15 years 3 months ago
Using background knowledge to speed reinforcement learning in physical agents
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...
Daniel G. Shapiro, Pat Langley, Ross D. Shachter