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» Measuring and Predicting Object Importance
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ICML
2005
IEEE
15 years 12 months ago
Predicting probability distributions for surf height using an ensemble of mixture density networks
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...
IPSN
2010
Springer
15 years 3 months ago
Practical modeling and prediction of radio coverage of indoor sensor networks
The robust operation of many sensor network applications depends on deploying relays to ensure wireless coverage. Radio mapping aims to predict network coverage based on a small n...
Octav Chipara, Gregory Hackmann, Chenyang Lu, Will...
BMCBI
2006
137views more  BMCBI 2006»
14 years 11 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
84
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BMCBI
2010
88views more  BMCBI 2010»
14 years 11 months ago
Proteome scanning to predict PDZ domain interactions using support vector machines
Background: PDZ domains mediate protein-protein interactions involved in important biological processes through the recognition of short linear motifs in their target proteins. Tw...
Shirley Hui, Gary D. Bader
EMMCVPR
2011
Springer
13 years 11 months ago
Optimization of Robust Loss Functions for Weakly-Labeled Image Taxonomies: An ImageNet Case Study
The recently proposed ImageNet dataset consists of several million images, each annotated with a single object category. However, these annotations may be imperfect, in the sense t...
Julian John McAuley, Arnau Ramisa, Tibério ...