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» Learning with Few Examples by Transferring Feature Relevance
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NIPS
2001
14 years 11 months ago
Discriminative Direction for Kernel Classifiers
In many scientific and engineering applications, detecting and understanding differences between two groups of examples can be reduced to a classical problem of training a classif...
Polina Golland
GECCO
2008
Springer
121views Optimization» more  GECCO 2008»
14 years 10 months ago
Fast rule representation for continuous attributes in genetics-based machine learning
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
Jaume Bacardit, Natalio Krasnogor
IJCAI
2007
14 years 11 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
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BXML
2003
14 years 11 months ago
An Instructional Component for Dynamic Course Generation and Delivery
: E-Learning offers the advantage of interactivity: an E-Learning system can adapt the learning materials to suit the learner’s personality and his goals, and it can react to the...
Carsten Ullrich
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
15 years 10 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales