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IROS
2007
IEEE
136views Robotics» more  IROS 2007»
16 years 23 days ago
Affordance-based imitation learning in robots
— In this paper we build an imitation learning algorithm for a humanoid robot on top of a general world model provided by learned object affordances. We consider that the robot h...
Manuel Lopes, Francisco S. Melo, Luis Montesano
ICML
2010
IEEE
15 years 7 months ago
On learning with kernels for unordered pairs
We propose and analyze two strategies to learn over unordered pairs with kernels, and provide a common theoretical framework to compare them. The strategies are related to methods...
Martial Hue, Jean-Philippe Vert
CVPR
2008
IEEE
16 years 8 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
PRL
2008
95views more  PRL 2008»
15 years 6 months ago
Semi-supervised learning by search of optimal target vector
We introduce a semi-supervised learning estimator which tends to the first kernel principal component as the number of labeled points vanishes. We show application of the proposed...
Leonardo Angelini, Daniele Marinazzo, Mario Pellic...
FOIKS
2008
Springer
15 years 8 months ago
Cost-Minimising Strategies for Data Labelling: Optimal Stopping and Active Learning
Supervised learning deals with the inference of a distribution over an output or label space Y conditioned on points in an observation space X , given a training dataset D of pair...
Christos Dimitrakakis, Christian Savu-Krohn