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» An Algebraic Approach to Inductive Learning
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IJAR
2010
113views more  IJAR 2010»
13 years 6 months ago
A geometric view on learning Bayesian network structures
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Milan Studený, Jirí Vomlel, Raymond ...
ICCS
2009
Springer
14 years 2 months ago
An Intelligent Tutoring System for Interactive Learning of Data Structures
Abstract. The high level of abstraction necessary to teach data structures and algorithmic schemes has been more than a hindrance to students. In order to make a proper approach to...
Rafael del Vado Vírseda, Pablo Ferná...
ICCBR
2001
Springer
14 years 5 days ago
A Case-Based Reasoning View of Automated Collaborative Filtering
From some perspectives Automated Collaborative Filtering (ACF) appears quite similar to Case-Based Reasoning (CBR). It works on data organised around users and assets that might be...
Conor Hayes, Padraig Cunningham, Barry Smyth
IJCAI
1989
13 years 8 months ago
A Critique of the Valiant Model
This paper considers the Valiant framework as it is applied to the task of learning logical concepts from random examples. It is argued that the current interpretation of this Val...
Wray L. Buntine
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
14 years 8 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...