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BMCBI
2008
171views more  BMCBI 2008»
13 years 7 months ago
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
Harri T. Kiiveri
INFOCOM
2011
IEEE
12 years 10 months ago
A robust optimization approach to backup network design with random failures
—This paper presents a scheme in which a dedicated backup network is designed to provide protection from random link failures. Upon a link failure in the primary network, traffi...
Matthew Johnston, Hyang-Won Lee, Eytan Modiano
CORR
2010
Springer
146views Education» more  CORR 2010»
13 years 7 months ago
Active Learning for Hidden Attributes in Networks
In many networks, vertices have hidden attributes that are correlated with the network's topology. For instance, in social networks, people are more likely to be friends if t...
Xiaoran Yan, Yaojia Zhu, Jean-Baptiste Rouquier, C...
SUM
2009
Springer
14 years 1 months ago
Modeling Unreliable Observations in Bayesian Networks by Credal Networks
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
Alessandro Antonucci, Alberto Piatti
ICFEM
2004
Springer
14 years 23 days ago
Linear Inequality LTL (iLTL): A Model Checker for Discrete Time Markov Chains
Abstract. We develop a way of analyzing the behavior of systems modeled using Discrete Time Markov Chains (DTMC). Specifically, we define iLTL, an LTL with linear inequalities on...
YoungMin Kwon, Gul Agha