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ICASSP
2010
IEEE
15 years 9 hour 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 9 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 12 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 4 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 months 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...