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» Learning From Ambiguous Examples
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ICML
2007
IEEE
16 years 5 months ago
Discriminative Gaussian process latent variable model for classification
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Raquel Urtasun, Trevor Darrell
ICRA
2002
IEEE
128views Robotics» more  ICRA 2002»
15 years 9 months ago
Generation of a Task Model by Integrating Multiple Observations of Human Demonstrations
This paper describes a new approach on how to teach a robot everyday manipulation tasks under the “Learning from Observation” framework. Most of the approaches so far assume t...
Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Kat...
157
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CLEF
2010
Springer
15 years 6 months ago
Visual Localization Using Global Visual Features and Vanishing Points
Abstract. This paper describes a visual localization approach for mobile robots. Robot localization is performed as location recognition. The approach uses global visual features (...
Olivier Saurer, Friedrich Fraundorfer, Marc Pollef...
IJCNN
2007
IEEE
15 years 11 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
ECIR
2009
Springer
15 years 2 months ago
Active Learning Strategies for Multi-Label Text Classification
Abstract. Active learning refers to the task of devising a ranking function that, given a classifier trained from relatively few training examples, ranks a set of additional unlabe...
Andrea Esuli, Fabrizio Sebastiani