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» The Convergence Rate of AdaBoost
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105
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NIPS
1996
15 years 2 months ago
Radial Basis Function Networks and Complexity Regularization in Function Learning
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Adam Krzyzak, Tamás Linder
80
Voted
FSTTCS
2008
Springer
15 years 1 months ago
Solvency Games
Abstract. We study the decision theory of a maximally risk-averse investor — one whose objective, in the face of stochastic uncertainties, is to minimize the probability of ever ...
Noam Berger, Nevin Kapur, Leonard J. Schulman, Vij...
ICASSP
2010
IEEE
15 years 26 days ago
Ergodic stochastic optimization algorithms for wireless communication and networking
— Ergodic stochastic optimization (ESO) algorithms are proposed to solve resource allocation problems that involve a random state and where optimality criteria are expressed in t...
Alejandro Ribeiro
GLOBECOM
2008
IEEE
15 years 25 days ago
Binary Consensus over Fading Channels: A Best Affine Estimation Approach
In this paper we consider a cooperative network that is trying to reach binary consensus over fading channels. We first characterize the impact of fading on network consensus by up...
Mehrzad Malmirchegini, Yongxiang Ruan, Yasamin Mos...
92
Voted
ACTA
2007
114views more  ACTA 2007»
15 years 24 days ago
Hybridization methods for the analysis of nonlinear systems
Abstract In this article, we describe some recent results on the hybridization methods for the analysis of nonlinear systems. The main idea of our hybridization approach is to appl...
Eugene Asarin, Thao Dang, Antoine Girard