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» A selective sampling approach to active feature selection
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ECIR
2003
Springer
13 years 11 months ago
Representative Sampling for Text Classification Using Support Vector Machines
In order to reduce human efforts, there has been increasing interest in applying active learning for training text classifiers. This paper describes a straightforward active learni...
Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi W...
ICIP
2006
IEEE
14 years 12 months ago
Foveated Analysis and Selection of Visual Fixations in Natural Scenes
The ability to automatically detect visually interesting regions in images has practical applications in the design of active machine vision systems. Analysis of the statistics of...
Umesh Rajashekar, Ian van der Linde, Alan C. Bovik...
JMLR
2010
162views more  JMLR 2010»
13 years 5 months ago
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...
ICMLA
2010
13 years 8 months ago
A New Approach to Classification with the Least Number of Features
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separati...
Sascha Klement, Thomas Martinetz
NIPS
2007
13 years 11 months ago
A general agnostic active learning algorithm
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni