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» Approximation Methods for Supervised Learning
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93
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CVPR
2005
IEEE
16 years 2 months ago
A Bayesian Hierarchical Model for Learning Natural Scene Categories
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
Fei-Fei Li 0002, Pietro Perona, California Institu...
ICML
2005
IEEE
16 years 1 months ago
Learn to weight terms in information retrieval using category information
How to assign appropriate weights to terms is one of the critical issues in information retrieval. Many term weighting schemes are unsupervised. They are either based on the empir...
Rong Jin, Joyce Y. Chai, Luo Si
95
Voted
PR
2006
101views more  PR 2006»
15 years 12 days ago
Feature-based approach to semi-supervised similarity learning
For the management of digital document collections, automatic database analysis still has ties to deal with semantic queries and abstract concepts that users are looking for. When...
Philippe Henri Gosselin, Matthieu Cord
104
Voted
RAS
2010
115views more  RAS 2010»
14 years 11 months ago
Learning grasping points with shape context
This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and ...
Jeannette Bohg, Danica Kragic
111
Voted
ICONIP
2009
14 years 10 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa