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» Learning for control from multiple demonstrations
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COGSR
2011
105views more  COGSR 2011»
14 years 4 months ago
Inductive rule learning on the knowledge level
We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be us...
Ute Schmid, Emanuel Kitzelmann
IROS
2009
IEEE
146views Robotics» more  IROS 2009»
15 years 4 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...
ICASSP
2007
IEEE
15 years 4 months ago
Wavelet Footprints and Sparse Bayesian Learning for DNA Copy Number Change Analysis
Alterations in the number of DNA copies are very common in tumor cells and may have a very important role in cancer development and progression. New array platforms provide means ...
Roger Pique-Regi, En-Shuo Tsau, Antonio Ortega, Ro...
ICTAI
2007
IEEE
15 years 4 months ago
Establishing Logical Rules from Empirical Data
We review a method of generating logical rules, or axioms, from empirical data. This method, using closed set properties of formal concept analysis, has been previously described ...
John L. Pfaltz
ICML
2009
IEEE
15 years 10 months ago
Factored conditional restricted Boltzmann Machines for modeling motion style
The Conditional Restricted Boltzmann Machine (CRBM) is a recently proposed model for time series that has a rich, distributed hidden state and permits simple, exact inference. We ...
Graham W. Taylor, Geoffrey E. Hinton