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FUIN
2006
95views more  FUIN 2006»
13 years 7 months ago
Bounds for Validation
In this paper we derive the bounds for Validation (known also as Hold-Out Estimate and Train-and-Test Method). We present the best possible bound in the case of 0-1 valued loss fun...
Wojciech Jaworski
TNN
1998
111views more  TNN 1998»
13 years 7 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos
WCNC
2008
IEEE
14 years 1 months ago
Exact BER Performance of Asynchronous MC-DS-CDMA over Nakagami-m Fading Channels
—In this contribution an accurate average bit error rate (BER) formula is derived for Nakagami-faded MC-DSCDMA in the context of asynchronous transmissions and random spreading s...
Besma Smida, Lajos Hanzo, Sofiène Affes
WSC
2004
13 years 8 months ago
A Large Deviations Perspective on Ordinal Optimization
We consider the problem of optimal allocation of computing budget to maximize the probability of correct selection in the ordinal optimization setting. This problem has been studi...
Peter W. Glynn, Sandeep Juneja
CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 7 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...