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» Learning on the Test Data: Leveraging Unseen Features
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SAC
2010
ACM
14 years 4 months ago
Feature selection for ordinal regression
Ordinal regression (also known as ordinal classification) is a supervised learning task that consists of automatically determining the implied rating of a data item on a fixed, ...
Stefano Baccianella, Andrea Esuli, Fabrizio Sebast...
SIGIR
2008
ACM
13 years 9 months ago
Learning to reduce the semantic gap in web image retrieval and annotation
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Changhu Wang, Lei Zhang 0001, Hong-Jiang Zhang
JMLR
2010
116views more  JMLR 2010»
13 years 4 months ago
Feature Selection, Association Rules Network and Theory Building
As the size and dimensionality of data sets increase, the task of feature selection has become increasingly important. In this paper we demonstrate how association rules can be us...
Sanjay Chawla
ICCV
2009
IEEE
15 years 2 months ago
Constrained Clustering by Spectral Kernel Learning
Clustering performance can often be greatly improved by leveraging side information. In this paper, we consider constrained clustering with pairwise constraints, which specify s...
Zhenguo Li, Jianzhuang Liu
ICIP
2005
IEEE
14 years 11 months ago
Feature selection with nonparametric statistics
In this paper we discuss a general framework for feature selection based on nonparametric statistics. The three stage approach we propose is based on the assumption that the avail...
Emanuele Franceschi, Francesca Odone, Fabrizio Sme...