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» Generalization Improvement in Multi-Objective Learning
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KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 1 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
WWW
2009
ACM
16 years 1 months ago
Learning to recognize reliable users and content in social media with coupled mutual reinforcement
Community Question Answering (CQA) has emerged as a popular forum for users to pose questions for other users to answer. Over the last few years, CQA portals such as Naver and Yah...
Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichte...
GECCO
2007
Springer
171views Optimization» more  GECCO 2007»
15 years 6 months ago
Toward a better understanding of rule initialisation and deletion
A number of heuristics have been used in Learning Classifier Systems to initialise parameters of new rules, to adjust fitness of parent rules when they generate offspring, and ...
Tim Kovacs, Larry Bull
IUI
2003
ACM
15 years 5 months ago
Interaction tactics for socially intelligent pedagogical agents
Guidebots, or animated pedagogical agents, can enhance interactive learning environments by promoting deeper learning and improve the learner's subjective experience. Guidebo...
W. Lewis Johnson
ECAI
2000
Springer
15 years 4 months ago
Naive Bayes and Exemplar-based Approaches to Word Sense Disambiguation Revisited
Abstract. This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar–basedclassification, on the Word Sens...
Gerard Escudero, Lluís Màrquez, Germ...