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» Semi-supervised Learning from General Unlabeled Data
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ESANN
2008
13 years 9 months ago
Generalized matrix learning vector quantizer for the analysis of spectral data
The analysis of spectral data constitutes new challenges for machine learning algorithms due to the functional nature of the data. Special attention is paid to the metric used in t...
Petra Schneider, Frank-Michael Schleif, Thomas Vil...
ISCI
1998
139views more  ISCI 1998»
13 years 7 months ago
A Rough Set Approach to Attribute Generalization in Data Mining
This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification...
Chien-Chung Chan
CVPR
2004
IEEE
14 years 9 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
ACL
2009
13 years 5 months ago
Distant supervision for relation extraction without labeled data
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
ICRA
2009
IEEE
179views Robotics» more  ICRA 2009»
14 years 2 months ago
Automatic weight learning for multiple data sources when learning from demonstration
— Traditional approaches to programming robots are generally inaccessible to non-robotics-experts. A promising exception is the Learning from Demonstration paradigm. Here a polic...
Brenna Argall, Brett Browning, Manuela M. Veloso