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» Feature subset selection bias for classification learning
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JAIR
2006
105views more  JAIR 2006»
14 years 9 months ago
Active Learning with Multiple Views
Active learners alleviate the burden of labeling large amounts of data by detecting and asking the user to label only the most informative examples in the domain. We focus here on...
Ion Muslea, Steven Minton, Craig A. Knoblock
AIRS
2010
Springer
14 years 7 months ago
Semantic Relation Extraction Based on Semi-supervised Learning
Many tasks of information extraction or natural language processing have a property that the data naturally consist of several views--disjoint subsets of features. Specifically, a ...
Haibo Li, Yutaka Matsuo, Mitsuru Ishizuka
IJCAI
2007
14 years 11 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
ICML
2003
IEEE
15 years 10 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
82
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ICPR
2010
IEEE
14 years 7 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...