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» A Robust Minimax Approach to Classification
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ICML
2004
IEEE
14 years 9 months ago
Robust feature induction for support vector machines
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
Rong Jin, Huan Liu
JMLR
2006
87views more  JMLR 2006»
13 years 9 months ago
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived f...
Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyy...
IJCV
2002
84views more  IJCV 2002»
13 years 8 months ago
Algorithmic Fusion for More Robust Feature Tracking
We present a framework for merging the results of independent featurebased motion trackers using a classification based approach. We demonstrate the efficacy of the framework usin...
Brendan McCane, Ben Galvin, Kevin Novins
JCDL
2005
ACM
175views Education» more  JCDL 2005»
14 years 2 months ago
Automated text classification using a multi-agent framework
Automatic text classification is an important operational problem in digital library practice. Most text classification efforts so far concentrated on developing centralized solut...
Yueyu Fu, Weimao Ke, Javed Mostafa
ICIAR
2009
Springer
13 years 6 months ago
A Robust Modular Wavelet Network Based Symbol Classifier
This paper presents a robust automatic shape classifier using modular wavelet networks (MWNs). A shape descriptor is constructed based on a combination of global geometric features...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...