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» Optimizing F-Measure with Support Vector Machines
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132
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ICPR
2010
IEEE
15 years 22 days ago
Learning the Kernel Combination for Object Categorization
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for ge...
Deyuan Zhang, Xiaolong Wang, Bingquan Liu
JMLR
2002
89views more  JMLR 2002»
15 years 2 months ago
A Robust Minimax Approach to Classification
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
127
Voted
SSPR
2004
Springer
15 years 8 months ago
Clustering Variable Length Sequences by Eigenvector Decomposition Using HMM
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Fatih Murat Porikli
159
Voted
IBPRIA
2009
Springer
15 years 7 months ago
Class Representative Visual Words for Category-Level Object Recognition
Recent works in object recognition often use visual words, i.e. vector quantized local descriptors extracted from the images. In this paper we present a novel method to build such ...
Roberto Javier López-Sastre, Tinne Tuytelaa...
130
Voted
BICOB
2010
Springer
15 years 25 days ago
Multiple Kernel Learning for Fold Recognition
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...
Huzefa Rangwala