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» Using model knowledge for learning inverse dynamics
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PAKDD
2000
ACM
128views Data Mining» more  PAKDD 2000»
14 years 14 days ago
Efficient Detection of Local Interactions in the Cascade Model
Detection of interactions among data items constitutes an essential part of knowledge discovery. The cascade model is a rule induction methodology using levelwise expansion of a la...
Takashi Okada
ICML
2000
IEEE
14 years 9 months ago
Discovering Homogeneous Regions in Spatial Data through Competition
If all features causing heterogeneity were observed, a mixture of experts approach (Jacobs et al., 1991) is likely to be superior to using a single model. When unobserved or very n...
Slobodan Vucetic, Zoran Obradovic
KI
2009
Springer
14 years 3 months ago
Presenting Proofs with Adapted Granularity
When mathematicians present proofs they usually adapt their explanations to their didactic goals and to the (assumed) knowledge of their addressees. Modern automated theorem prover...
Marvin Schiller, Christoph Benzmüller
ICAIL
2003
ACM
14 years 2 months ago
Predicting Outcomes of Case-Based Legal Arguments
In this paper, we introduce IBP, an algorithm that combines g with an abstract domain model and case-based reasoning techniques to predict the outcome of case-based legal argument...
Stefanie Brüninghaus, Kevin D. Ashley
ILP
2003
Springer
14 years 2 months ago
Comparative Evaluation of Approaches to Propositionalization
Propositionalization has already been shown to be a particularly promising approach for robustly and effectively handling relational data sets for knowledge discovery. In this pap...
Mark-A. Krogel, Simon Rawles, Filip Zelezný...