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ICML
2009
IEEE
16 years 5 months ago
Trajectory prediction: learning to map situations to robot trajectories
Trajectory planning and optimization is a fundamental problem in articulated robotics. Algorithms used typically for this problem compute optimal trajectories from scratch in a ne...
Nikolay Jetchev, Marc Toussaint
138
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ICML
2009
IEEE
16 years 5 months ago
Prototype vector machine for large scale semi-supervised learning
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
Kai Zhang, James T. Kwok, Bahram Parvin
ICML
2009
IEEE
16 years 5 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
124
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ICML
2007
IEEE
16 years 5 months ago
On learning linear ranking functions for beam search
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Yuehua Xu, Alan Fern
ICML
2007
IEEE
16 years 5 months ago
Learning nonparametric kernel matrices from pairwise constraints
Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Som...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu
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