@inproceedings{ba567ab42db84255aa130fe72f3f1ad0,
title = "Large margin maximum entropy machines for classifier combination",
abstract = "Majority voting in classifier combination treats all base classifiers equally without considering their performance differences. By analyzing the constraints imposed by the margins of an ensemble classifier, a set of weights can be computed to give better prediction than the majority voting. We propose a regularized classifier combination strategy that maximize the entropy of probability weights assigned to base classifiers subjected to the margin constraints of the ensemble classifier. Furthermore, we show that a sparse solution with a set of support vectors for ensemble classifier can be obtained.",
keywords = "Pattern recognition, Wavelet analysis, Conferences",
author = "Zhili Wu and Chun-hung Li and Victor Cheng",
note = "Publisher copyright: {\textcopyright} 2008, IEEE ; 2008 International Conference on Wavelet Analysis and Pattern Recognition ; Conference date: 30-08-2008 Through 31-08-2008",
year = "2008",
month = aug,
day = "31",
doi = "10.1109/ICWAPR.2008.4635808",
language = "English",
isbn = "9781424422395",
volume = "1",
series = "International Conference on Wavelet Analysis and Pattern Recognition",
publisher = "IEEE Canada",
pages = "378--383",
booktitle = "2008 International Conference on Wavelet Analysis and Pattern Recognition",
address = "Canada",
}