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ICASSP
2010
IEEE
14 years 10 months ago
Training a support vector machine to classify signals in a real environment given clean training data
When building a classifier from clean training data for a particular test environment, knowledge about the environmental noise and channel should be taken into account. We propos...
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum...
EMNLP
2009
14 years 7 months ago
Weighted Alignment Matrices for Statistical Machine Translation
Current statistical machine translation systems usually extract rules from bilingual corpora annotated with 1-best alignments. They are prone to learn noisy rules due to alignment...
Yang Liu, Tian Xia, Xinyan Xiao, Qun Liu
CORR
2008
Springer
114views Education» more  CORR 2008»
14 years 9 months ago
Support Vector Machine Classification with Indefinite Kernels
In this paper, we propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our...
Ronny Luss, Alexandre d'Aspremont
COLT
1999
Springer
15 years 2 months ago
Uniform-Distribution Attribute Noise Learnability
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
Nader H. Bshouty, Jeffrey C. Jackson, Christino Ta...
FLAIRS
2008
15 years 2 days ago
Machine Learning to Predict the Incidence of Retinopathy of Prematurity
Retinopathy of Prematurity (ROP) is a disorder afflicting prematurely born infants. ROP can be positively diagnosed a few weeks after birth. The goal of this study is to build an ...
Aniket Ray, Vikas Kumar, Balaraman Ravindran, Ling...