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NEUROSCIENCE
2001
Springer
15 years 11 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
LWA
2004
15 years 8 months ago
Modeling Rule Precision
This paper reports first results of an empirical study of the precision of classification rules on an independent test set. We generated a large number of rules using a general co...
Johannes Fürnkranz
ICML
2006
IEEE
16 years 7 months ago
On Bayesian bounds
We show that several important Bayesian bounds studied in machine learning, both in the batch as well as the online setting, arise by an application of a simple compression lemma....
Arindam Banerjee
ICML
2001
IEEE
16 years 7 months ago
Inducing Partially-Defined Instances with Evolutionary Algorithms
This paper addresses the issue of reducing the storage requirements on Instance-Based Learning algorithms. Algorithms proposed by other researches use heuristics to prune instance...
Josep Maria Garrell i Guiu, Xavier Llorà
FLAIRS
2008
15 years 9 months ago
Selecting Minority Examples from Misclassified Data for Over-Sampling
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
Jorge de la Calleja, Olac Fuentes, Jesús Go...