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126
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PKDD
2010
Springer
143views Data Mining» more  PKDD 2010»
14 years 10 months ago
A Unified Approach to Active Dual Supervision for Labeling Features and Examples
Abstract. When faced with the task of building accurate classifiers, active learning is often a beneficial tool for minimizing the requisite costs of human annotation. Traditional ...
Josh Attenberg, Prem Melville, Foster J. Provost
88
Voted
UAI
2004
15 years 1 months ago
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Omid Madani, Daniel J. Lizotte, Russell Greiner
WSCG
2004
188views more  WSCG 2004»
15 years 1 months ago
Recognition of Motor Imagery Electroencephalography Using Independent Component Analysis and Machine Classifiers
Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used as neural input signals ...
Chih-I. Hung, Po-Lei Lee, Yu-Te Wu, Hui-Yun Chen, ...
82
Voted
CHI
2001
ACM
16 years 22 days ago
Time Aura: interfaces for pacing
Historically one of the visions for human-computer symbiosis has been to augment human intelligence and extend people's cognitive abilities. In this paper, we present two vis...
Lena Mamykina, Elizabeth D. Mynatt, Michael A. Ter...
128
Voted
IJCAI
2001
15 years 1 months ago
Active Learning for Class Probability Estimation and Ranking
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Maytal Saar-Tsechansky, Foster J. Provost