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NIPS
2004
15 years 3 months ago
Support Vector Classification with Input Data Uncertainty
This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
Jinbo Bi, Tong Zhang
PAMI
2008
190views more  PAMI 2008»
15 years 2 months ago
Scene Classification Using a Hybrid Generative/Discriminative Approach
We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail we are given a set ...
Anna Bosch, Andrew Zisserman, Xavier Muñoz
141
Voted
BMCBI
2011
14 years 6 months ago
Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data
Background: Classification and variable selection play an important role in knowledge discovery in highdimensional data. Although Support Vector Machine (SVM) algorithms are among...
Natalia Becker, Grischa Toedt, Peter Lichter, Axel...
ICML
1998
IEEE
16 years 3 months ago
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
Moisés Goldszmidt, Nir Friedman, Thomas J. ...
157
Voted
CVPR
2010
IEEE
15 years 5 months ago
Classification and Clustering via Dictionary Learning with Structured Incoherence
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...