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» Using Stochastic Grammars to Learn Robotic Tasks
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CVPR
2007
IEEE
16 years 1 months ago
Fast Terrain Classification Using Variable-Length Representation for Autonomous Navigation
We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
AR
2007
204views more  AR 2007»
14 years 12 months ago
Action recognition and understanding through motor primitives
In robotics, recognition of human activity has been used extensively for robot task learning through imitation and demonstration. However, there has not been much work on modeling...
Isabel Serrano Vicente, Ville Kyrki, Danica Kragic...
ATAL
2007
Springer
15 years 3 months ago
Confidence-based policy learning from demonstration using Gaussian mixture models
We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
Sonia Chernova, Manuela M. Veloso
ICML
2010
IEEE
15 years 24 days ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
CORR
2011
Springer
211views Education» more  CORR 2011»
14 years 3 months ago
Labeling 3D scenes for Personal Assistant Robots
—Inexpensive RGB-D cameras that give an RGB image together with depth data have become widely available. We use this data to build 3D point clouds of a full scene. In this paper,...
Hema Swetha Koppula, Abhishek Anand, Thorsten Joac...