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» Parameterized Learning Complexity
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ICML
2009
IEEE
16 years 5 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
149
Voted
ICML
2007
IEEE
16 years 5 months ago
Classifying matrices with a spectral regularization
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...
Ryota Tomioka, Kazuyuki Aihara
ICML
2008
IEEE
16 years 5 months ago
Detecting statistical interactions with additive groves of trees
Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be expressed as the sum of lower-d...
Daria Sorokina, Rich Caruana, Mirek Riedewald, Dan...
122
Voted
ICML
2006
IEEE
16 years 5 months ago
Efficient inference on sequence segmentation models
Sequence segmentation is a flexible and highly accurate mechanism for modeling several applications. Inference on segmentation models involves dynamic programming computations tha...
Sunita Sarawagi
147
Voted
ICML
2006
IEEE
16 years 5 months ago
Statistical debugging: simultaneous identification of multiple bugs
We describe a statistical approach to software debugging in the presence of multiple bugs. Due to sparse sampling issues and complex interaction between program predicates, many g...
Alice X. Zheng, Michael I. Jordan, Ben Liblit, May...