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IDEAL
2000
Springer
13 years 11 months ago
Quantization of Continuous Input Variables for Binary Classification
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
Michal Skubacz, Jaakko Hollmén
TPDS
2010
135views more  TPDS 2010»
13 years 6 months ago
Maximizing Service Reliability in Distributed Computing Systems with Random Node Failures: Theory and Implementation
—In distributed computing systems (DCSs) where server nodes can fail permanently with nonzero probability, the system performance can be assessed by means of the service reliabil...
Jorge E. Pezoa, Sagar Dhakal, Majeed M. Hayat
SOCO
2010
Springer
13 years 2 months ago
Designing multilayer perceptrons using a Guided Saw-tooth Evolutionary Programming Algorithm
In this paper, a diversity generating mechanism is proposed for an Evolutionary Programming (EP) algorithm that determines the basic structure of Multilayer Perceptron classifiers ...
Pedro Antonio Gutiérrez, César Herv&...
TSP
2008
149views more  TSP 2008»
13 years 7 months ago
Decentralized Quantized Kalman Filtering With Scalable Communication Cost
Estimation and tracking of generally nonstationary Markov processes is of paramount importance for applications such as localization and navigation. In this context, ad hoc wireles...
Eric J. Msechu, Stergios I. Roumeliotis, Alejandro...
ACISP
2009
Springer
14 years 2 months ago
Building Key-Private Public-Key Encryption Schemes
In the setting of identity-based encryption with multiple trusted authorities, TA anonymity formally models the inability of an adversary to distinguish two ciphertexts correspondi...
Kenneth G. Paterson, Sriramkrishnan Srinivasan