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» Learning Probabilistic Models of Relational Structure
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112
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ICML
2007
IEEE
16 years 1 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
101
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EDUTAINMENT
2007
Springer
15 years 6 months ago
ISRST: An Interest Based Storytelling Model Using Rhetorical Relations
Most storytelling model approaches consider stories formed by sequences of a particular type of event. These sequences are mostly constructed using the inherent temporal characteri...
Arturo Nakasone, Mitsuru Ishizuka
FSS
2008
110views more  FSS 2008»
15 years 16 days ago
Learning valued preference structures for solving classification problems
This paper introduces a new approach to classification which combines pairwise decomposition techniques with ideas and tools from fuzzy preference modeling. More specifically, our...
Eyke Hüllermeier, Klaus Brinker
ATAL
2006
Springer
15 years 4 months ago
Rule value reinforcement learning for cognitive agents
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
Christopher Child, Kostas Stathis
HUC
2010
Springer
15 years 20 days ago
Bayesian recognition of motion related activities with inertial sensors
This work presents the design and evaluation of an activity recognition system for seven important motion related activities. The only sensor used is an Inertial Measurement Unit ...
Korbinian Frank, Maria Josefa Vera Nadales, Patric...