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ILP
2003
Springer
14 years 23 days ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon
ML
2006
ACM
110views Machine Learning» more  ML 2006»
13 years 7 months ago
Distribution-based aggregation for relational learning with identifier attributes
Abstract Identifier attributes--very high-dimensional categorical attributes such as particular product ids or people's names--rarely are incorporated in statistical modeling....
Claudia Perlich, Foster J. Provost
ISOLA
2010
Springer
13 years 6 months ago
LivingKnowledge: Kernel Methods for Relational Learning and Semantic Modeling
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
Alessandro Moschitti
ESWS
2008
Springer
13 years 9 months ago
Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We exten...
Christoph Kiefer, Abraham Bernstein, André ...
WSDM
2012
ACM
325views Data Mining» more  WSDM 2012»
12 years 3 months ago
Coupled temporal scoping of relational facts
Recent research has made significant advances in automatically constructing knowledge bases by extracting relational facts (e.g., Bill Clinton-presidentOf-US) from large text cor...
Partha Pratim Talukdar, Derry Tanti Wijaya, Tom Mi...