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IJRR
2011
218views more  IJRR 2011»
15 years 1 months ago
Motion planning under uncertainty for robotic tasks with long time horizons
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...
MA
2010
Springer
94views Communications» more  MA 2010»
15 years 5 months ago
On sparse estimation for semiparametric linear transformation models
: Semiparametric linear transformation models have received much attention due to its high flexibility in modeling survival data. A useful estimating equation procedure was recent...
Hao Helen Zhang, Wenbin Lu, Hansheng Wang
SIGMOD
2006
ACM
219views Database» more  SIGMOD 2006»
16 years 6 months ago
Modeling skew in data streams
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...
Flip Korn, S. Muthukrishnan, Yihua Wu
CVPR
2010
IEEE
16 years 2 months ago
The chains model for detecting parts by their context
Detecting an object part relies on two sources of information - the appearance of the part itself, and the context supplied by surrounding parts. In this paper we consider problem...
Leonid Karlinsky, Michael Dinerstein, Daniel Harar...
TMI
2010
175views more  TMI 2010»
15 years 1 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu