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CVPR
2005
IEEE
15 years 20 days ago
Pruning Training Sets for Learning of Object Categories
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...
BCB
2010
175views Bioinformatics» more  BCB 2010»
13 years 5 months ago
Gene set analysis using principal components
We present a new method for identifying gene sets associated with labeled samples, where the labels can be case versus control, or genotype differences. Existing approaches to thi...
Isa Kemal Pakatci, Wei Wang, Leonard McMillan
JMLR
2006
103views more  JMLR 2006»
13 years 10 months ago
Pattern Recognition for Conditionally Independent Data
In this work we consider the task of relaxing the i.i.d. assumption in pattern recognition (or classification), aiming to make existing learning algorithms applicable to a wider r...
Daniil Ryabko
PAMI
2010
225views more  PAMI 2010»
13 years 5 months ago
Semi-Supervised Classification via Local Spline Regression
Abstract--This paper presents local spline regression for semisupervised classification. The core idea in our approach is to introduce splines developed in Sobolev space to map the...
Shiming Xiang, Feiping Nie, Changshui Zhang
ICPR
2010
IEEE
14 years 2 months ago
Underwater Mine Classification with Imperfect Labels
A new algorithm for performing classification with imperfectly labeled data is presented. The proposed approach is motivated by the insight that the average prediction of a group ...
David Williams