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143
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GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
15 years 8 months ago
Bayesian network structure learning using cooperative coevolution
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
Olivier Barrière, Evelyne Lutton, Pierre-He...
124
Voted
CDC
2008
IEEE
15 years 10 months ago
Simultaneous placement and assignment for exploration in mobile backbone networks
Abstract— This paper presents new algorithms for conducting cooperative sensing using a mobile backbone network. This hierarchical sensing approach combines backbone nodes, which...
Emily M. Craparo, Jonathan P. How, Eytan Modiano
163
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CPAIOR
2011
Springer
14 years 7 months ago
Upgrading Shortest Paths in Networks
We introduce the Upgrading Shortest Paths Problem, a new combinatorial problem for improving network connectivity with a wide range of applications from multicast communication to ...
Bistra N. Dilkina, Katherine J. Lai, Carla P. Gome...
130
Voted
NIPS
2008
15 years 5 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey
116
Voted
TNN
2008
181views more  TNN 2008»
15 years 3 months ago
Optimized Approximation Algorithm in Neural Networks Without Overfitting
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
Yinyin Liu, Janusz A. Starzyk, Zhen Zhu