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» Using Stochastic Grammars to Learn Robotic Tasks
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IROS
2009
IEEE
146views Robotics» more  IROS 2009»
14 years 3 months ago
Robust constraint-consistent learning
— Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently...
Matthew Howard, Stefan Klanke, Michael Gienger, Ch...
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
13 years 6 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
MIRRORBOT
2005
Springer
154views Robotics» more  MIRRORBOT 2005»
14 years 2 months ago
Spatial Representation and Navigation in a Bio-inspired Robot
Abstract. A biologically inspired computational model of rodent representation–based (locale) navigation is presented. The model combines visual input in the form of realistic tw...
Denis Sheynikhovich, Ricardo Chavarriaga, Thomas S...
AR
2006
95views more  AR 2006»
13 years 8 months ago
Adaptive body schema for robotic tool-use
The development and expression of many higher level cognitive functions, such as imitation, spatial perception, and tool-use relies on a multi-modal representation of the body kno...
Cota Nabeshima, Yasuo Kuniyoshi, Max Lungarella
CVPR
2010
IEEE
14 years 5 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun