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» An Instance Selection Approach to Multiple Instance Learning
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ICPR
2004
IEEE
14 years 10 months ago
Feature Subset Selection using ICA for Classifying Emphysema in HRCT Images
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
Mithun Nagendra Prasad, Arcot Sowmya, Inge Koch
CVPR
2011
IEEE
13 years 6 months ago
Dynamic Batch Mode Active Learning
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
Shayok Chakraborty, Vineeth Balasubramanian, Sethu...
ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
14 years 1 months ago
Arbiter Meta-Learning with Dynamic Selection of Classifiers and Its Experimental Investigation
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classifica...
Alexey Tsymbal, Seppo Puuronen, Vagan Y. Terziyan
ICTAI
2010
IEEE
13 years 6 months ago
Continuous Search in Constraint Programming
This work presents the concept of Continuous Search (CS), which objective is to allow any user to eventually get their constraint solver achieving a top performance on their proble...
Alejandro Arbelaez, Youssef Hamadi, Michèle...
TNN
2008
178views more  TNN 2008»
13 years 8 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen