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» A Model Selection Approach for Local Learning
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ICML
1999
IEEE
14 years 8 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
BTW
2005
Springer
113views Database» more  BTW 2005»
14 years 1 months ago
A Learning Optimizer for a Federated Database Management System
: Optimizers in modern DBMSs utilize a cost model to choose an efficient query execution plan (QEP) among all possible ones for a given query. The accuracy of the cost estimates de...
Stephan Ewen, Michael Ortega-Binderberger, Volker ...
NIPS
2007
13 years 9 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
PPSN
2004
Springer
14 years 29 days ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
CVPR
2011
IEEE
13 years 3 months ago
Supervised Local Subspace Learning for Continuous Head Pose Estimation
Head pose estimation from images has recently attracted much attention in computer vision due to its diverse applications in face recognition, driver monitoring and human computer...
Dong Huang, Markus Storer, Fernando DelaTorre, Hor...