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» Information Theory, Inference, and Learning Algorithms
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KDD
1995
ACM
135views Data Mining» more  KDD 1995»
13 years 11 months ago
Rough Sets Similarity-Based Learning from Databases
Manydata mining algorithms developed recently are based on inductive learning methods. Very few are based on similarity-based learning. However, similarity-based learning accrues ...
Xiaohua Hu, Nick Cercone
CORR
2008
Springer
143views Education» more  CORR 2008»
13 years 8 months ago
Join Bayes Nets: A new type of Bayes net for relational data
Many real-world data are maintained in relational format, with different tables storing information about entities and their links or relationships. The structure (schema) of the ...
Oliver Schulte, Hassan Khosravi, Flavia Moser, Mar...
GECCO
2006
Springer
153views Optimization» more  GECCO 2006»
13 years 11 months ago
Analysis of the difficulty of learning goal-scoring behaviour for robot soccer
Learning goal-scoring behaviour from scratch for simulated robot soccer is considered to be a very difficult problem, and is often achieved by endowing players with an innate set ...
Jeff Riley, Victor Ciesielski
IJON
2007
88views more  IJON 2007»
13 years 7 months ago
Information maximization in face processing
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
Marian Stewart Bartlett
AAAI
1994
13 years 9 months ago
Learning to Reason
We introduce a new framework for the study of reasoning. The Learning (in order) to Reason approach developed here views learning as an integral part of the inference process, and ...
Roni Khardon, Dan Roth