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ICML
2006
IEEE
16 years 8 months ago
Efficient learning of Naive Bayes classifiers under class-conditional classification noise
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Christophe Nicolas Magnan, François Denis, ...
ICML
2002
IEEE
16 years 8 months ago
Learning to Share Distributed Probabilistic Beliefs
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Christopher Leckie, Kotagiri Ramamohanarao
ICASSP
2009
IEEE
16 years 2 months ago
Fingerprint matching based on distance metric learning
This paper considers a method for learning a distance metric in a fingerprinting system which identifies a query content by measuring the distance between the fingerprint of th...
Dalwon Jang, Chang D. Yoo
ECTEL
2007
Springer
16 years 1 months ago
Relevance Ranking Metrics for Learning Objects
— The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevan...
Xavier Ochoa, Erik Duval
APPROX
2005
Springer
80views Algorithms» more  APPROX 2005»
16 years 1 months ago
On Learning Random DNF Formulas Under the Uniform Distribution
Abstract: We study the average-case learnability of DNF formulas in the model of learning from uniformly distributed random examples. We define a natural model of random monotone ...
Jeffrey C. Jackson, Rocco A. Servedio