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» Structure learning of Bayesian networks using constraints
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AINTEC
2005
Springer
15 years 10 months ago
Users and Services in Intelligent Networks
— We present a vision of an Intelligent Network in which users dynamically indicate their requests for services, and formulate needs in terms of Quality of Service (QoS) and pric...
Erol Gelenbe
ICML
2006
IEEE
16 years 5 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
CVPR
2001
IEEE
16 years 6 months ago
A Spherical Eye from Multiple Cameras (Makes Better Models of the World)
This paper describes an imagingsystem that has been designed specifically for the purpose of recovering egomotion and structure from video. The system consists of six cameras in a...
Patrick Baker, Cornelia Fermüller, Yiannis Al...
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 7 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
RECOMB
2004
Springer
16 years 5 months ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...