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» Dimensions of machine learning in design
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EGICE
2006
14 years 27 days ago
Evolutionary Generation of Implicative Fuzzy Rules for Design Knowledge Representation
Abstract. In knowledge representation by fuzzy rule based systems two reasoning mechanisms can be distinguished: conjunction-based and implication-based inference. Both approaches ...
Mark Freischlad, Martina Schnellenbach-Held, Torbe...
ITS
2000
Springer
137views Multimedia» more  ITS 2000»
14 years 25 days ago
Design Principles for a System to Teach Problem Solving by Modelling
This paper presents an approach to the design of a learning environment in a mathematical domain (elementary combinatorics) where problem solving is based more on modelling than o...
Gérard Tisseau, Hélène Giroir...
JMLR
2008
209views more  JMLR 2008»
13 years 9 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
ML
2008
ACM
110views Machine Learning» more  ML 2008»
13 years 7 months ago
A theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum, Nathan Srebro
ICML
2006
IEEE
14 years 10 months ago
On a theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum