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IJAR
2010
130views more  IJAR 2010»
15 years 13 days ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
ICCV
2007
IEEE
16 years 3 months ago
Optimization and Learning for Registration of Moving Dynamic Textures
We address the problem of registering a sequence of images in a moving dynamic texture video. This involves optimization with respect to camera motion, the average image, and the ...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
BTW
2005
Springer
113views Database» more  BTW 2005»
15 years 7 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 ...
WSDM
2010
ACM
129views Data Mining» more  WSDM 2010»
15 years 11 months ago
Early Exit Optimizations for Additive Machine Learned Ranking Systems
Berkant Barla Cambazoglu, Hugo Zaragoza, Olivier C...
CORR
2010
Springer
125views Education» more  CORR 2010»
15 years 2 months ago
Near-Optimal Bayesian Active Learning with Noisy Observations
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
Daniel Golovin, Andreas Krause, Debajyoti Ray