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DIS
2006
Springer
15 years 1 months ago
Optimal Bayesian 2D-Discretization for Variable Ranking in Regression
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Marc Boullé, Carine Hue
ICCV
2009
IEEE
14 years 7 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
JMLR
2010
128views more  JMLR 2010»
14 years 4 months ago
Fluid Dynamics Models for Low Rank Discriminant Analysis
We consider the problem of reducing the dimensionality of labeled data for classification. Unfortunately, the optimal approach of finding the low-dimensional projection with minim...
Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
IDA
2009
Springer
15 years 4 months ago
Bayesian Robust PCA for Incomplete Data
Abstract. We present a probabilistic model for robust principal component analysis (PCA) in which the observation noise is modelled by Student-t distributions that are independent ...
Jaakko Luttinen, Alexander Ilin, Juha Karhunen
DGO
2007
133views Education» more  DGO 2007»
14 years 11 months ago
A toolbox for the choice of indicator classes for ranking of watersheds
There has been considerable work on determining a suitable method to accomplish a satisfactory ordering of a group of objects, when there are multiple evaluation criteria. A weigh...
K. Sham Bhat