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FUIN
2008
108views more  FUIN 2008»
13 years 6 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
14 years 7 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»
13 years 7 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
12 years 11 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
14 years 7 days 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