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131
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ICML
2009
IEEE
15 years 9 months ago
Rule learning with monotonicity constraints
In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing ...
Wojciech Kotlowski, Roman Slowinski
CVPR
2004
IEEE
16 years 4 months ago
Is Bottom-Up Attention Useful for Object Recognition?
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Ueli Rutishauser, Dirk Walther, Christof Koch, Pie...
146
Voted
EMNLP
2007
15 years 4 months ago
LEDIR: An Unsupervised Algorithm for Learning Directionality of Inference Rules
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
Rahul Bhagat, Patrick Pantel, Eduard H. Hovy
102
Voted
PR
2007
148views more  PR 2007»
15 years 2 months ago
Learning the best subset of local features for face recognition
We propose a novel, local feature-based face representation method based on twostage subset selection where the first stage finds the informative regions and the second stage ...
Berk Gökberk, M. Okan Irfanoglu, Lale Akarun,...
147
Voted
ANNPR
2006
Springer
15 years 6 months ago
Visual Classification of Images by Learning Geometric Appearances Through Boosting
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...