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ECML
2004
Springer
13 years 10 months ago
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
Rong Jin, Huan Liu
ICDM
2009
IEEE
199views Data Mining» more  ICDM 2009»
13 years 11 months ago
Active Learning with Adaptive Heterogeneous Ensembles
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Zhenyu Lu, Xindong Wu, Josh Bongard
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 6 months ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard
PCM
2007
Springer
114views Multimedia» more  PCM 2007»
13 years 11 months ago
Random Convolution Ensembles
A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is g...
Michael Mayo
ICIC
2007
Springer
13 years 11 months ago
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal...
Huanhuan Chen, Xin Yao