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» Learning on the Test Data: Leveraging Unseen Features
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ICML
2004
IEEE
14 years 10 months ago
Testing the significance of attribute interactions
Attribute interactions are the irreducible dependencies between attributes. Interactions underlie feature relevance and selection, the structure of joint probability and classific...
Aleks Jakulin, Ivan Bratko
CVPR
2004
IEEE
14 years 11 months ago
Learning Distance Functions for Image Retrieval
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
PRL
2008
118views more  PRL 2008»
13 years 8 months ago
Bayes Machines for binary classification
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Daniel Hernández-Lobato, José Miguel...
ICANN
2003
Springer
14 years 2 months ago
Sparse Coding with Invariance Constraints
We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set...
Heiko Wersing, Julian Eggert, Edgar Körner
NIPS
2008
13 years 10 months ago
Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization
The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...
Liu Yang, Rong Jin, Rahul Sukthankar