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» Approximate algorithms for neural-Bayesian approaches
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JCSS
2010
146views more  JCSS 2010»
14 years 8 months ago
Connected facility location via random facility sampling and core detouring
We present a simple randomized algorithmic framework for connected facility location problems. The basic idea is as follows: We run a black-box approximation algorithm for the unc...
Friedrich Eisenbrand, Fabrizio Grandoni, Thomas Ro...
PAMI
2008
145views more  PAMI 2008»
14 years 9 months ago
Latent-Space Variational Bayes
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
JaeMo Sung, Zoubin Ghahramani, Sung Yang Bang
IPCO
2007
108views Optimization» more  IPCO 2007»
14 years 11 months ago
Robust Combinatorial Optimization with Exponential Scenarios
Following the well-studied two-stage optimization framework for stochastic optimization [15, 18], we study approximation algorithms for robust two-stage optimization problems with ...
Uriel Feige, Kamal Jain, Mohammad Mahdian, Vahab S...
ICDE
2006
IEEE
176views Database» more  ICDE 2006»
15 years 11 months ago
Mondrian Multidimensional K-Anonymity
K-Anonymity has been proposed as a mechanism for protecting privacy in microdata publishing, and numerous recoding "models" have been considered for achieving kanonymity...
Kristen LeFevre, David J. DeWitt, Raghu Ramakrishn...
ICML
2008
IEEE
15 years 10 months ago
Learning to classify with missing and corrupted features
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
Ofer Dekel, Ohad Shamir