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COLT
1994
Springer
13 years 11 months ago
Bayesian Inductive Logic Programming
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
Stephen Muggleton
PPDP
2007
Springer
14 years 1 months ago
Higher-order semantic labelling for inductive datatype systems
We give a novel transformation for proving termination of higher-order rewrite systems in the format of Inductive Data Type Systems (IDTSs) by Blanqui, Jouannaud and Okada. The tr...
Makoto Hamana
ECCV
2008
Springer
13 years 8 months ago
Multi-thread Parsing for Recognizing Complex Events in Videos
This paper presents a probabilistic grammar approach to the recognition of complex events in videos. Firstly, based on the original motion features, a rule induction algorithm is a...
Zhang Zhang, Kaiqi Huang, Tieniu Tan
NAACL
2010
13 years 5 months ago
Painless Unsupervised Learning with Features
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
CORR
2010
Springer
147views Education» more  CORR 2010»
13 years 7 months ago
Learning Probabilistic Hierarchical Task Networks to Capture User Preferences
While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning use...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...