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ESANN
2007
13 years 9 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
VEE
2009
ACM
171views Virtualization» more  VEE 2009»
14 years 2 months ago
Dynamic memory balancing for virtual machines
Virtualization essentially enables multiple operating systems and applications to run on one physical computer by multiplexing hardware resources. A key motivation for applying vi...
Weiming Zhao, Zhenlin Wang
ICONIP
2007
13 years 9 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor
ACL
1998
13 years 9 months ago
Machine Translation with a Stochastic Grammatical Channel
We introduce a stochastic grammatical channel model for machine translation, that synthesizes several desirable characteristics of both statistical and grammatical machine transla...
Dekai Wu, Hongsing Wong
BMCBI
2010
159views more  BMCBI 2010»
13 years 8 months ago
Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
Alvaro J. González, Li Liao