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ICPR
2008
IEEE
13 years 11 months ago
RANSAC-SVM for large-scale datasets
Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
Kenji Watanabe, Takio Kurita
PE
2008
Springer
109views Optimization» more  PE 2008»
13 years 4 months ago
A conditional probability approach to M/G/1-like queues
Following up on a recently renewed interest in computational methods for M/G/1-type processes, this paper considers an M/G/1-like system in which the service time distribution is ...
Alexandre Brandwajn, Hongyun Wang
EMNLP
2008
13 years 6 months ago
Phrase Translation Probabilities with ITG Priors and Smoothing as Learning Objective
The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heurist...
Markos Mylonakis, Khalil Sima'an
UAI
2004
13 years 6 months ago
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Peter Hooper
ICML
2006
IEEE
14 years 5 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara