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ICML
2006
IEEE
16 years 7 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, ...
ECTEL
2007
Springer
16 years 24 days ago
Representing Computer-Supported Collaborative Learning Macro-scripts using IMS Learning Design
IMS Learning Design (LD) is a specification that aims at computationally representing any learning process. However, the possibilities of LD to represent collaborative learning sce...
Davinia Hernández Leo, Daniel Burgos, Colin...
CEC
2010
IEEE
15 years 7 months ago
Principles of protein processing for a self-organising associative memory
The evolution of Artificial Intelligence has passed through many phases over the years, going from rigorous mathematical grounding to more intuitive bio-inspired approaches. Despit...
Omer Qadir, Jerry Liu, Jon Timmis, Gianluca Tempes...
ECTEL
2007
Springer
16 years 24 days ago
Resolving Variations in Learning Spaces for Experiential Learning
Today, systems should react based on explicit demands from the learner or even proactively react based on changes in the working environment. The success of this type of systems de...
Eric Ras
ICGI
2004
Springer
16 years 4 hour ago
Learning Stochastic Finite Automata
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We report here a number of results concerning the learnability of th...
Colin de la Higuera, José Oncina