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125
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DIS
2010
Springer
15 years 23 days ago
Speeding Up and Boosting Diverse Density Learning
Abstract. In multi-instance learning, each example is described by a bag of instances instead of a single feature vector. In this paper, we revisit the idea of performing multi-ins...
James R. Foulds, Eibe Frank
146
Voted
ISBI
2011
IEEE
14 years 5 months ago
Hippocampus segmentation using a stable maximum likelihood classifier ensemble algorithm
We develop a new algorithm to segment the hippocampus from MR images. Our method uses a new classifier ensemble algorithm to correct segmentation errors produced by a multi-atlas...
Hongzhi Wang, Jung Wook Suh, Sandhitsu R. Das, Mur...
COLT
1999
Springer
15 years 6 months ago
Multiclass Learning, Boosting, and Error-Correcting Codes
We focus on methods to solve multiclass learning problems by using only simple and efficient binary learners. We investigate the approach of Dietterich and Bakiri [2] based on er...
Venkatesan Guruswami, Amit Sahai
115
Voted
CORR
2000
Springer
132views Education» more  CORR 2000»
15 years 2 months ago
A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
This paper describes a set of comparative experiments, including cross{corpus evaluation, between ve alternative algorithms for supervised Word Sense Disambiguation (WSD), namely ...
Gerard Escudero, Lluís Màrquez, Germ...
99
Voted
ICML
2006
IEEE
16 years 3 months ago
Multiclass boosting with repartitioning
A multiclass classification problem can be reduced to a collection of binary problems with the aid of a coding matrix. The quality of the final solution, which is an ensemble of b...
Ling Li